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Philip Hans Franses

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2013. "Are Forecast Updates Progressive?," MPRA Paper 46387, University Library of Munich, Germany.

    Mentioned in:

    1. What Have You Been Reading?
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-06-12 00:47:00
  2. Franses, Ph.H.B.F., 2016. "Yet another look at MIDAS regression," Econometric Institute Research Papers EI2016-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Mentioned in:

    1. Some Suggested Reading for October
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2016-10-02 23:53:00
  3. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2012. "Evaluating Macroeconomic Forecasts: A Concise Review of Some Recent Developments," Documentos de Trabajo del ICAE 2012-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    Mentioned in:

    1. What I Learned Last Week
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-10-13 09:19:00
  4. Franses, Ph.H.B.F., 2019. "Professional Forecasters and January," Econometric Institute Research Papers EI2019-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Mentioned in:

    1. Back to School Reading
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2019-09-01 13:40:00
  5. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Mentioned in:

    1. Guest Contribution: "An assessment of the US jobless recovery through a non-linear Okun’s law"
      by Menzie Chinn in Econbrowser on 2012-12-18 04:05:06
  6. Author Profile
    1. Top Forecasting Institutions and Researchers According to IDEAS!
      by Clive Jones in Business Forecasting on 2013-06-28 01:43:46

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Bart Hobijn & Philip Hans Franses, 2000. "Asymptotically perfect and relative convergence of productivity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 59-81.

    Mentioned in:

    1. Asymptotically perfect and relative convergence of productivity (Journal of Applied Econometrics 2000) in ReplicationWiki ()
  2. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.

    Mentioned in:

    1. A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables (Journal of Applied Econometrics 2000) in ReplicationWiki ()
  3. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.

    Mentioned in:

    1. Testing for ARCH in the presence of additive outliers (Journal of Applied Econometrics 1999) in ReplicationWiki ()
  4. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827.

    Mentioned in:

    1. A multi-level panel STAR model for US manufacturing sectors (Journal of Applied Econometrics 2005) in ReplicationWiki ()
  5. Zsolt Sándor & Philip Hans Franses, 2009. "Consumer price evaluations through choice experiments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 517-535, April.

    Mentioned in:

    1. Consumer price evaluations through choice experiments (Journal of Applied Econometrics 2009) in ReplicationWiki ()
  6. Richard Paap & Philip Hans Franses & Marco Van Der Leij, 2002. "Modelling and forecasting level shifts in absolute returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 601-616.

    Mentioned in:

    1. Modelling and forecasting level shifts in absolute returns (Journal of Applied Econometrics 2002) in ReplicationWiki ()

Working papers

  1. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

    Cited by:

    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    3. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    4. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    5. Heymann, Fabian & Milojevic, Tatjana & Covatariu, Andrei & Verma, Piyush, 2023. "Digitalization in decarbonizing electricity systems – Phenomena, regional aspects, stakeholders, use cases, challenges and policy options," Energy, Elsevier, vol. 262(PB).
    6. Oscar Espinosa & Valeria Bejarano & Jeferson Ramos & Boris Martínez, 2023. "Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021," Health Economics Review, Springer, vol. 13(1), pages 1-20, December.
    7. Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
    8. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    9. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    10. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review," Energies, MDPI, vol. 16(6), pages 1-23, March.
    11. Paul Ghelasi & Florian Ziel, 2025. "A data-driven merit order: Learning a fundamental electricity price model," Papers 2501.02963, arXiv.org.
    12. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org.
    13. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    14. Xiaoqian Wang & Yanfei Kang & Rob J Hyndman & Feng Li, 2020. "Distributed ARIMA Models for Ultra-long Time Series," Monash Econometrics and Business Statistics Working Papers 29/20, Monash University, Department of Econometrics and Business Statistics.
    15. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
    16. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    17. Elalem, Yara Kayyali & Maier, Sebastian & Seifert, Ralf W., 2023. "A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1874-1894.
    18. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    19. Michael Pedersen, 2024. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," Papers 2404.04105, arXiv.org.
    20. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    21. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
    22. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    23. Mutele, Litshedzani & Carranza, Emmanuel John M., 2024. "Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Afr," Resources Policy, Elsevier, vol. 93(C).
    24. Takahashi, Carlos Kazunari & Figueiredo, Júlio César Bastos de & Scornavacca, Eusebio, 2024. "Investigating the diffusion of innovation: A comprehensive study of successive diffusion processes through analysis of search trends, patent records, and academic publications," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    25. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    26. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
    27. Said Rosli & Sulaimi Mardhiati & Majid Rohayu Ab & Aini Ainoriza Mohd & Olanrele Olusegun Olaopin & Akinsomi Omokolade, 2024. "Evaluating Market Attributes and Housing Affordability: Gaining Perspective on Future Value Trends," Real Estate Management and Valuation, Sciendo, vol. 32(3), pages 87-100.
    28. Ghelasi, Paul & Ziel, Florian, 2024. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 581-596.
    29. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    30. Shanshan Wang & Shih‐Chih Chen & Mohd Helmi Ali & Ming‐Lang Tseng, 2024. "Nexus of environmental, social, and governance performance in China‐listed companies: Disclosure and green bond issuance," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 1647-1660, March.
    31. Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    32. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    33. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
    34. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    35. Pan Tang & Yuwei Zhang, 2024. "China's business cycle forecasting: a machine learning approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2783-2811, November.
    36. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
    37. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    38. Bernhard Tröster & Ulrich Gunter, 2023. "The Financialization of Coffee, Cocoa and Cotton Value Chains: The Role of Physical Actors," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1550-1574, November.
    39. Jacek Batóg & Barbara Batóg & Magdalena Mojsiewicz & Przemysław Pluskota, 2024. "Electrification of Public Urban Transport: Funding Opportunities, Bus Fleet, and Energy Use Forecasts for Poland," Energies, MDPI, vol. 17(23), pages 1-20, December.
    40. Martin McCarthy, Stephen Snudden, 2024. "Forecasts of Period-Average Exchange Rates: New Insights from Real-Time Daily Data," LCERPA Working Papers jc0148, Laurier Centre for Economic Research and Policy Analysis, revised Oct 2024.
    41. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    42. Rai, Amit & Shrivastava, Ashish & Jana, Kartick C., 2023. "Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting," Energy, Elsevier, vol. 263(PC).
    43. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    44. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Oleksandr Dluhopolskyi & Artur Dmowski & Marzena Cichorzewska, 2022. "The Migration Influence on the Forecasting of Health Care Budget Expenditures in the Direction of Sustainability: Case of Ukraine," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    45. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    46. Andrea Savio & Luigi De Giovanni & Mariangela Guidolin, 2022. "Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    47. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    48. Fernández, Joaquín Delgado & Menci, Sergio Potenciano & Lee, Chul Min & Rieger, Alexander & Fridgen, Gilbert, 2022. "Privacy-preserving federated learning for residential short-term load forecasting," Applied Energy, Elsevier, vol. 326(C).
    49. Emmanuel Senyo Fianu, 2022. "Analyzing and Forecasting Multi-Commodity Prices Using Variants of Mode Decomposition-Based Extreme Learning Machine Hybridization Approach," Forecasting, MDPI, vol. 4(2), pages 1-27, June.
    50. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    51. Ca’ Zorzi, Michele & Rubaszek, Michał, 2023. "How many fundamentals should we include in the behavioral equilibrium exchange rate model?," Economic Modelling, Elsevier, vol. 118(C).
    52. Radovan Šomplák & Veronika Smejkalová & Martin Rosecký & Lenka Szásziová & Vlastimír Nevrlý & Dušan Hrabec & Martin Pavlas, 2023. "Comprehensive Review on Waste Generation Modeling," Sustainability, MDPI, vol. 15(4), pages 1-29, February.
    53. Racek, Daniel & Thurner, Paul W. & Davidson, Brittany I. & Zhu, Xiao Xiang & Kauermann, Göran, 2024. "Conflict forecasting using remote sensing data: An application to the Syrian civil war," International Journal of Forecasting, Elsevier, vol. 40(1), pages 373-391.
    54. Huang, Congzhi & Yang, Mengyuan, 2023. "Memory long and short term time series network for ultra-short-term photovoltaic power forecasting," Energy, Elsevier, vol. 279(C).
    55. Raja, Aitazaz Ali & Pinson, Pierre & Kazempour, Jalal & Grammatico, Sergio, 2024. "A market for trading forecasts: A wagering mechanism," International Journal of Forecasting, Elsevier, vol. 40(1), pages 142-159.
    56. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    57. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).
    58. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    59. Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024. "On the (Mis)Use of Machine Learning with Panel Data," Papers 2411.09218, arXiv.org.
    60. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    61. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    62. Jeroen Rombouts & Marie Ternes & Ines Wilms, 2024. "Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning," Papers 2402.09033, arXiv.org, revised May 2024.
    63. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.
    64. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.

  2. Li, W. & Fok, D. & Franses, Ph.H.B.F., 2019. "Forecasting own brand sales: Does incorporating competition help?," Econometric Institute Research Papers EI2019-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Oliver Schaer & Nikolaos Kourentzes & Robert Fildes, 2022. "Predictive competitive intelligence with prerelease online search traffic," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3823-3839, October.

  3. Franses, Ph.H.B.F., 2019. "IMA(1,1) as a new benchmark for forecast evaluation," Econometric Institute Research Papers EI2019-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Heidorn, Thomas & Schäfer, Niklas, 2020. "Euro-Benchmarkreform - Neue Referenzzinssätze in der Eurozone," Frankfurt School - Working Paper Series 228, Frankfurt School of Finance and Management.

  4. Bhaghoe, S. & Ooft, G. & Franses, Ph.H.B.F., 2019. "Estimates of quarterly GDP growth using MIDAS regressions," Econometric Institute Research Papers EI2019-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.

  5. van Dieijen, M.J. & Borah, A. & Tellis, G.J. & Franses, Ph.H.B.F., 2019. "Big Data Analysis of Volatility Spillovers of Brands across Social Media and Stock Markets," Econometric Institute Research Papers EI-1691, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Halil D Kaya & Abhinav Maramraju & Anish Nallapu, 2023. "Social Media, Trading Volume, Volatility And Stock Prices," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 40-50, December.
    2. Apostolidis, Chrysostomos & Devine, Anthony & Jabbar, Abdul, 2022. "From chalk to clicks – The impact of (rapid) technology adoption on employee emotions in the higher education sector," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

  6. Franses, Ph.H.B.F. & S. Vasilev (Simeon), 2019. "Real GDP growth in Africa, 1963-2016," Econometric Institute Research Papers EI2019-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Mattera, Raffaele & Franses, Philip Hans, 2023. "Are African business cycles synchronized? Evidence from spatio-temporal modeling," Economic Modelling, Elsevier, vol. 128(C).
    2. Franses, Ph.H.B.F., 2019. "Do African economies grow similarly?," Econometric Institute Research Papers EI2019-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  7. Franses, Ph.H.B.F. & Wiemann, T., 2018. "Intertemporal Similarity of Economic Time Series," Econometric Institute Research Papers EI2018-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F., 2019. "Do African economies grow similarly?," Econometric Institute Research Papers EI2019-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Aleksandra Rutkowska & Magdalena Szyszko, 2022. "New DTW Windows Type for Forward- and Backward-Lookingness Examination. Application for Inflation Expectation," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 701-718, February.

  8. van den Hengel, G. & Franses, Ph.H.B.F., 2018. "Forecasting social conflicts in Africa using an Epidemic Type Aftershock Sequence model," Econometric Institute Research Papers EI2018-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

  9. Franses, Ph.H.B.F. & Janssens, E., 2017. "Spurious Principal Components," Econometric Institute Research Papers EI2017-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Tobias Hartl, 2020. "Macroeconomic Forecasting with Fractional Factor Models," Papers 2005.04897, arXiv.org.

  10. Franses, Ph.H.B.F. & Janssens, E., 2016. "Recovering historical inflation data from postal stamps prices," Econometric Institute Research Papers EI2016-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Chia-Lin Chang, 2020. "Editorial for Applied Econometrics," JRFM, MDPI, vol. 13(9), pages 1-5, August.
    2. Franses, Philip Hans & Janssens, Eva, 2018. "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 261-292.

  11. Franses, Ph.H.B.F., 2016. "Yet another look at MIDAS regression," Econometric Institute Research Papers EI2016-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Adeniji Sesan Oluseyi & Timilehin John Olasehinde & Gamaliel O. Eweke, 2017. "The Impact of Money Supply on Nigeria Economy: A Comparison of Mixed Data Sampling (MIDAS) and ARDL Approach," EuroEconomica, Danubius University of Galati, issue 2(36), pages 123-134, November.

  12. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2015. "Specification Testing in Hawkes Models," Tinbergen Institute Discussion Papers 15-086/III, Tinbergen Institute.

    Cited by:

    1. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Molina-Muñoz, Jesús & Mora-Valencia, Andrés & Perote, Javier, 2020. "Market-crash forecasting based on the dynamics of the alpha-stable distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    3. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2015. "Exploiting Spillovers to forecast Crashes," Tinbergen Institute Discussion Papers 15-118/III, Tinbergen Institute.
    4. Marcello Rambaldi & Vladimir Filimonov & Fabrizio Lillo, 2016. "Detection of intensity bursts using Hawkes processes: an application to high frequency financial data," Papers 1610.05383, arXiv.org.

  13. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F. & de Bruijn, L.P., 2015. "Benchmarking judgmentally adjusted forecasts," Econometric Institute Research Papers EI2015-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Meyler, Aidan, 2020. "Forecast performance in the ECB SPF: ability or chance?," Working Paper Series 2371, European Central Bank.

  14. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2015. "Exploiting Spillovers to forecast Crashes," Tinbergen Institute Discussion Papers 15-118/III, Tinbergen Institute.

    Cited by:

    1. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Molina-Muñoz, Jesús & Mora-Valencia, Andrés & Perote, Javier, 2020. "Market-crash forecasting based on the dynamics of the alpha-stable distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    3. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).

  15. Bodeutsch, D.S. & Franses, Ph.H.B.F., 2015. "Risk attitudes in company boardrooms in a developing country," Econometric Institute Research Papers EI 2015-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Denice Bodeutsch & Philip Hans Franses, 2016. "Risk Attitudes In The Board Room And Company Performance: Evidence For An Emerging Economy," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-14, December.

  16. Dulam, T.W. & Franses, Ph.H.B.F., 2014. "Microeconomic determinants of skilled migration: The case of Suriname," Econometric Institute Research Papers EI 2014-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F., 2015. "Return migration of high skilled workers," Econometric Institute Research Papers 78065, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  17. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2014. "Interpreting Financial Market Crashes as Earthquakes: A New early Warning System for Medium Term Crashes," Tinbergen Institute Discussion Papers 14-067/III, Tinbergen Institute.

    Cited by:

    1. Zhi-Qiang Jiang & Gang-Jin Wang & Askery Canabarro & Boris Podobnik & Chi Xie & H. Eugene Stanley & Wei-Xing Zhou, 2016. "Short term prediction of extreme returns based on the recurrence interval analysis," Papers 1610.08230, arXiv.org.
    2. Dissanayake, Pushpa & Flock, Teresa & Meier, Johanna & Sibbertsen, Philipp, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Hannover Economic Papers (HEP) dp-690, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Specification Testing in Hawkes Models," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 139-171.
    5. Molina-Muñoz, Jesús & Mora-Valencia, Andrés & Perote, Javier, 2020. "Market-crash forecasting based on the dynamics of the alpha-stable distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    6. Tomlinson, Matthew F. & Greenwood, David & Mucha-Kruczyński, Marcin, 2024. "2T-POT Hawkes model for left- and right-tail conditional quantile forecasts of financial log returns: Out-of-sample comparison of conditional EVT models," International Journal of Forecasting, Elsevier, vol. 40(1), pages 324-347.
    7. Connor Oxenhorn, 2022. "A Multivariate Hawkes Process Model for Stablecoin-Cryptocurrency Depegging Event Dynamics," Papers 2205.06338, arXiv.org.
    8. Li, Wei-Zhen & Zhai, Jin-Rui & Jiang, Zhi-Qiang & Wang, Gang-Jin & Zhou, Wei-Xing, 2022. "Predicting tail events in a RIA-EVT-Copula framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    9. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    10. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2015. "Exploiting Spillovers to forecast Crashes," Tinbergen Institute Discussion Papers 15-118/III, Tinbergen Institute.
    11. Jagielski, Maciej & Kutner, Ryszard & Sornette, Didier, 2017. "Theory of earthquakes interevent times applied to financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 68-73.
    12. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    13. Lleo, Sebastien & Zhitlukhin, Mikhail & Ziemba, William, 2021. "Using a mean changing stochastic processes exit-entry model for stock market long-short prediction," LSE Research Online Documents on Economics 118875, London School of Economics and Political Science, LSE Library.
    14. Lleo, Sebastien & Ziemba, William, 2017. "A tale of two indexes: predicting equity market downturns in China," LSE Research Online Documents on Economics 85131, London School of Economics and Political Science, LSE Library.
    15. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    16. Maciej Jagielski & Ryszard Kutner & Didier Sornette, 2016. "Theory of earthquakes interevent times applied to financial markets," Papers 1610.08921, arXiv.org, revised Oct 2016.
    17. Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
    18. Hossein Dastkhan, 2021. "Network‐based early warning system to predict financial crisis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 594-616, January.

  18. Bodeutsch, D.S. & Franses, Ph.H.B.F., 2014. "The Stock Exchange of Suriname: Returns, Volatility, Correlations and Weak-form Efficiency," Econometric Institute Research Papers EI 2014-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Ooft, G. & Bhaghoe, S. & Franses, Ph.H.B.F., 2019. "Forecasting Annual Inflation in Suriname," Econometric Institute Research Papers EI2019-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Qureshi, Fiza & Kutan, Ali M. & Ismail, Izlin & Gee, Chan Sok, 2017. "Mutual funds and stock market volatility: An empirical analysis of Asian emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 176-192.

  19. Franses, Ph.H.B.F., 2014. "The life cycle of social media," Econometric Institute Research Papers EI 2014-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Xing Yu Zhu & Abdul Razaque Chhachhar, 2016. "Descriptive Analysis Regarding Use of Wechat among University Students in China," Asian Social Science, Canadian Center of Science and Education, vol. 12(2), pages 151-151, February.

  20. de Bruijn, L.P. & Segers, R. & Franses, Ph.H.B.F., 2014. "A Novel Approach to Measuring Consumer Confidence," Econometric Institute Research Papers EI 2014-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Wu, Hung-Che & Ai, Chi-Han & Cheng, Ching-Chan, 2019. "Experiential quality, experiential psychological states and experiential outcomes in an unmanned convenience store," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 409-420.
    2. Chi-Wei Su & Xian-Li Meng & Ran Tao & Muhammad Umar, 2023. "Chinese consumer confidence: A catalyst for the outbound tourism expenditure?," Tourism Economics, , vol. 29(3), pages 696-717, May.

  21. Bodeutsch, D.S. & Franses, Ph.H.B.F., 2013. "Size and value effects in Suriname," Econometric Institute Research Papers EI 2013-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Denice Bodeutsch & Philip Hans Franses, 2016. "Risk Attitudes In The Board Room And Company Performance: Evidence For An Emerging Economy," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-14, December.
    2. Ruan, Qingsong & Yang, Bingchan, 2017. "The effects of common risk factors on stock returns: A detrended cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 362-374.
    3. French, Joseph J. & Taborda, Rodrigo, 2018. "Disentangling the relationship between liquidity and returns in Latin America," Global Finance Journal, Elsevier, vol. 36(C), pages 23-40.

  22. Franses, Ph.H.B.F., 2013. "Are we in a bubble? A simple time-series-based diagnostic," Econometric Institute Research Papers EI 2013-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2016. "Use of unit root methods in early warning of financial crises," Bank of Finland Research Discussion Papers 27/2016, Bank of Finland.
    2. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2017. "Use of unit root methods in early warning of financial crises," ESRB Working Paper Series 45, European Systemic Risk Board.

  23. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2012. "Evaluating Macroeconomic Forecasts: A Concise Review of Some Recent Developments," Working Papers in Economics 12/12, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Miquel Clar-Lopez & Jordi López-Tamayo & Raúl Ramos, 2014. "Unemployment forecasts, time varying coefficient models and the Okun’s law in Spanish regions," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 247-262.
    2. Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2020. "Nonlinear forecast combinations: An example using euro-area real GDP growth," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 579-589.
    3. Mihaela Simionescu (Bratu), 2014. "The Performance of Predictions Based on the Dobrescu Macromodel for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 179-195, October.
    4. Mihaela BRATU (SIMIONESCU), 2012. "A Strategy To Improve The Gdp Index Forcasts In Romania Using Moving Average Models Of Historical Errors Of The Dobrescu Macromodel," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 128-138, December.
    5. Simionescu Mihaela, 2015. "Kalman Filter or VAR Models to Predict Unemployment Rate in Romania?," Naše gospodarstvo/Our economy, Sciendo, vol. 61(3), pages 3-21, June.
    6. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
    7. Bratu Mihaela, 2013. "An Evaluation Of Usa Unemployment Rate Forecasts In Terms Of Accuracy And Bias. Empirical Methods To Improve The Forecasts Accuracy," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 170-180, February.
    8. Claeys, Peter & Cimadomo, Jacopo & Poplawski Ribeiro, Marcos, 2014. "How do financial institutions forecast sovereign spreads?," Working Paper Series 1750, European Central Bank.
    9. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.

  24. Franses, Ph.H.B.F. & Legerstee, R., 2012. "Statistical Institutes and Economic Prosperity," Econometric Institute Research Papers 32410, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Philip Hans Franses & Eva Janssens, 2017. "Recovering Historical Inflation Data from Postage Stamps Prices," JRFM, MDPI, vol. 10(4), pages 1-11, November.

  25. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.

    Cited by:

    1. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.

  26. de Groot, E.A. & Franses, Ph.H.B.F., 2012. "Do Commercial Real Estate Prices Have Predictive Content for GDP," Econometric Institute Research Papers EI 2012-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Sidong Zhao & Weiwei Li & Kaixu Zhao & Ping Zhang, 2021. "Change Characteristics and Multilevel Influencing Factors of Real Estate Inventory—Case Studies from 35 Key Cities in China," Land, MDPI, vol. 10(9), pages 1-29, September.
    2. Sidong Zhao & Kaixu Zhao & Ping Zhang, 2021. "Spatial Inequality in China’s Housing Market and the Driving Mechanism," Land, MDPI, vol. 10(8), pages 1-33, August.

  27. Franses, Ph.H.B.F. & Knecht, W., 2012. "The Late 1970's Bubble in Dutch Collectible Postage Stamps," Econometric Institute Research Papers EI 2013-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Fromentin, Vincent & Pecchioli, Bruno & Moroz, David, 2024. "Time-varying causality among whisky, wine, and equity markets," Finance Research Letters, Elsevier, vol. 63(C).

  28. de Groot, E.A. & Renes, S. & Segers, R. & Franses, Ph.H.B.F., 2012. "Risk Perception and Decision-Making by the Corporate Elite: Empirical Evidence for Netherlands-based Companies," ERIM Report Series Research in Management ERS-2012-013, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Denice Bodeutsch & Philip Hans Franses, 2016. "Risk Attitudes In The Board Room And Company Performance: Evidence For An Emerging Economy," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-14, December.
    2. Bodeutsch, D.S. & Franses, Ph.H.B.F., 2015. "Risk attitudes in company boardrooms in a developing country," Econometric Institute Research Papers EI 2015-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  29. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2011. "Evaluating Individual and Mean Non-Replicable Forecasts," Working Papers in Economics 11/16, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.

  30. Sanne Lise Blauw & Philip Hans Franses, 2011. "The Impact of Mobile Telephone Use on Economic Development of Households in Uganda," Tinbergen Institute Discussion Papers 11-152/4, Tinbergen Institute.

    Cited by:

    1. Desiere, Sam & Vellema, Wytse & D’Haese, Marijke, 2014. "A validity assessment of the Progress out of Poverty Index (PPI) for Rwanda," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182727, European Association of Agricultural Economists.
    2. Zheng, Xuyuan & Lu, Haiyang, 2021. "Does ICT change household decision-making power of the left-behind women? A Case from China," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    3. Ward, Michael R. & Zheng, Shilin, 2014. "Mobile telecommunications infrastructure and economic growth: Evidence from China," 25th European Regional ITS Conference, Brussels 2014 101405, International Telecommunications Society (ITS).
    4. Desiere, Sam & Vellema, Wytse & D’Haese, Marijke, 2015. "A validity assessment of the Progress out of Poverty Index (PPI)™," Evaluation and Program Planning, Elsevier, vol. 49(C), pages 10-18.
    5. Yazid Abdullahi Abubakar & Jay Mitra & Adeyeye Mercy Modupe, 2018. "Mobile Telephony and New Business Formation Rates in BRICS and Beyond: Does Human Capital Matter?," Journal of Entrepreneurship and Innovation in Emerging Economies, Entrepreneurship Development Institute of India, vol. 4(2), pages 137-158, July.

  31. Dulam, T.W. & Franses, Ph.H.B.F., 2011. "Emigration, wage differentials and brain drain: The case of Suriname," Econometric Institute Research Papers EI 2011-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F., 2015. "Return migration of high skilled workers," Econometric Institute Research Papers 78065, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Dulam, T.W. & Franses, Ph.H.B.F., 2014. "Microeconomic determinants of skilled migration: The case of Suriname," Econometric Institute Research Papers EI 2014-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  32. Franses, Ph.H.B.F. & Legerstee, R. & Paap, R., 2011. "Estimating Loss Functions of Experts," Econometric Institute Research Papers EI2011-42, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Nicolaas van der Wath, 2013. "Comparing the BER’s forecasts," Working Papers 23/2013, Stellenbosch University, Department of Economics.
    2. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.

  33. Heleen Mees & Philip Hans Franses, 2011. "Are Chinese Individuals prone to Money Illusion?," Tinbergen Institute Discussion Papers 11-149/4, Tinbergen Institute, revised 25 Mar 2014.

    Cited by:

    1. Elisa Darriet & Marianne Guille & Jean-Christophe Vergnaud & Mariko Shimizu, 2020. "Money illusion, financial literacy and numeracy: experimental evidence," Post-Print hal-02310038, HAL.
    2. Murota, Ryu-ichiro, 2019. "Negative interest rate policy in a permanent liquidity trap," MPRA Paper 93498, University Library of Munich, Germany.
    3. Thomas A. Stephens & Jean-Robert Tyran, 2016. "Money Illusion and Household Finance," Discussion Papers 16-14, University of Copenhagen. Department of Economics.

  34. Philip Hans Franses & Chia-Lin Chang & Michael McAleer, 2011. "Analyzing Fixed-event Forecast Revisions," Working Papers in Economics 11/25, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    2. Tara M. Sinclair & Jeff Messina & Herman Stekler, 2014. "What Can We Learn From Revisions to the Greenbook Forecasts?," Working Papers 2014-14, The George Washington University, Institute for International Economic Policy.
    3. Chang, Chia-Lin & Ke, Yu-Pei, 2014. "Testing Price Pressure, Information, Feedback Trading, and Smoothing Effects for Energy Exchange Traded Funds," MPRA Paper 57625, University Library of Munich, Germany.
    4. Tian, Jing & Goodwin, Thomas, 2018. "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers 2018-04, University of Tasmania, Tasmanian School of Business and Economics.
    5. Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2021. "Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 290-314.

  35. Legerstee, R. & Franses, Ph.H.B.F. & Paap, R., 2011. "Do experts incorporate statistical model forecasts and should they?," Econometric Institute Research Papers EI2011-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Rianne Legerstee & Philip Hans Franses, 2011. "Do Experts' SKU Forecasts improve after Feedback?," Tinbergen Institute Discussion Papers 11-135/4, Tinbergen Institute.

  36. Legerstee, R. & Franses, Ph.H.B.F., 2011. "Do experts' SKU forecasts improve after feedback?," Econometric Institute Research Papers EI2011-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    4. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
    5. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.

  37. Franses, Ph.H.B.F. & Lede, M.M., 2010. "Diffusion of Original and Counterfeit Products in a Developing Country," Econometric Institute Research Papers EI 2010-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Philip Hans Franses & Madesta Lede, 2017. "Adoption of Falsified Medical Products in a Low-Income Country: Empirical Evidence for Suriname," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    2. Franses, Ph.H.B.F. & Lede, M.M., 2010. "Diffusion of counterfeit medical products in a developing country: Empirical evidence for Suriname," Econometric Institute Research Papers EI 2010-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  38. Donkers, A.C.D. & van Diepen, M. & Franses, Ph.H.B.F., 2010. "Do Charities Get More when They Ask More Often? Evidence from a Unique Field Experiment," ERIM Report Series Research in Management ERS-2010-015-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Maja Adena & Anselm Hager, 2024. "Does Online Fundraising Increase Charitable Giving? A Nationwide Field Experiment on Facebook," Rationality and Competition Discussion Paper Series 493, CRC TRR 190 Rationality and Competition.
    2. Smith, Sarah & Scharf, Kimberley & Wilhelm, Mark, 2017. "Lift and Shift: The Effect of Fundraising Interventions in Charity Space and Time," CEPR Discussion Papers 12338, C.E.P.R. Discussion Papers.
    3. Carrieri, Vincenzo & Principe, Francesco, 2020. "WHO and for How Long? An Empirical Analysis of the Consumers' Response to Red Meat Warning," IZA Discussion Papers 13882, Institute of Labor Economics (IZA).
    4. Bar-El, Ronen & Hatsor, Limor & Snir, Avichai, 2024. "An experiment on donations, personal stories, and bad luck," European Journal of Political Economy, Elsevier, vol. 84(C).
    5. Gallier, Carlo & Goeschl, Timo & Kesternich, Martin & Lohse, Johannes & Reif, Christiane & Römer, Daniel, 2019. "Inter-charity competition under spatial differentiation: Sorting, crowding, and spillovers," ZEW Discussion Papers 19-039, ZEW - Leibniz Centre for European Economic Research.
    6. Goetz, Alexander & Mayr, Harald & Schubert, Renate, 2024. "One thing leads to another: Evidence on the scope and persistence of behavioral spillovers," Journal of Public Economics, Elsevier, vol. 236(C).
    7. Jan Schmitz, 2021. "Is Charitable Giving a Zero-Sum Game? The Effect of Competition Between Charities on Giving Behavior," Management Science, INFORMS, vol. 67(10), pages 6333-6349, October.
    8. Gani Aldashev & Marco Marini & Thierry Verdier, 2017. "Samaritan Bundles: Inefficient Clustering in NGO Projects," Working Papers ECARES ECARES 2017-12, ULB -- Universite Libre de Bruxelles.
    9. Avichai Snir & Ronen Bar-El & Limor Hatsor, 2023. "An experiment on Donations, Personal Stories, and Bad Luck," Working Papers 2023-01, Bar-Ilan University, Department of Economics.
    10. Mayo, Jennifer, 2021. "How do big gifts affect rival charities and their donors?," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 575-597.
    11. Mette T. Damgaard, 2020. "A decade of nudging: What have we learned?," Economics Working Papers 2020-07, Department of Economics and Business Economics, Aarhus University.
    12. Damgaard, Mette Trier, 2021. "A decade of nudging: What have we learned?," Nationaløkonomisk tidsskrift, Nationaløkonomisk Forening, vol. 2021(1), pages 1-21.
    13. Carrieri, V.; & Principe, F.;, 2018. "WHO and for how long? An empirical analysis of the consumers’ response to red meat warning," Health, Econometrics and Data Group (HEDG) Working Papers 18/08, HEDG, c/o Department of Economics, University of York.

  39. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," Working Papers in Economics 10/09, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Constantin ANGHELACHE & Cristina SACALA, 2016. "Theoretical model used for macroeconomic analysis," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(7), pages 57-60, July.

  40. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Are Forecast Updates Progressive?," Working Papers in Economics 10/12, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Michael McAleer & Felix Chan & Les Oxley, 2013. "Modelling and Simulation: An Overview," KIER Working Papers 865, Kyoto University, Institute of Economic Research.

  41. Lam, K.Y. & Koning, A.J. & Franses, Ph.H.B.F., 2010. "Ranking Models in Conjoint Analysis," Econometric Institute Research Papers EI 2010-51, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Kornprom Satraphand & Supeecha Panichpathom, 2018. "Willingness to Pay for Senior Wellness Center," ERES eres2018_21, European Real Estate Society (ERES).

  42. Chia-Lin Chang & Philip Hans Franses & Michael McAleer & Les Oxley, 2010. "What Makes a Great Journal Great in the Sciences? Which Came First, the Chicken or the Egg?," Working Papers in Economics 10/75, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Chang, C-L. & McAleer, M.J., 2014. "Just How Good are the Top Three Journals in Finance? An Assessment Based on Quantity and Quality Citations," Econometric Institute Research Papers EI2014-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Chia-Lin Chang & Michael McAleer, 2014. "Ranking Economics and Econometrics ISI Journals by Quality Weighted Citations," Documentos de Trabajo del ICAE 2014-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Chang, C-L. & McAleer, M.J., 2011. "Citations and Impact of ISI Tourism and Hospitality Journals," Econometric Institute Research Papers EI2011-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Walters, William H., 2014. "Do Article Influence scores overestimate the citation impact of social science journals in subfields that are related to higher-impact natural science disciplines?," Journal of Informetrics, Elsevier, vol. 8(2), pages 421-430.
    5. Chia-Lin Chang & Michael McAleer & Les Oxley, 2013. "Coercive Journal Self Citations, Impact Factor, Journal Influence and Article Influence," KIER Working Papers 852, Kyoto University, Institute of Economic Research.
    6. Chang, C-L. & McAleer, M.J., 2011. "How Should Journal Quality be Ranked? An Application to Agricultural, Energy, Environment and Resource Economics," Econometric Institute Research Papers EI 2011-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Chia-Lin Chang & Michael McAleer, 2012. "Ranking Journal Quality by Harmonic Mean of Ranks: An Application to ISI Statistics & Probability," Documentos de Trabajo del ICAE 2012-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    8. Chia-Lin Chang & Michael McAleer, 2013. "Ranking Leading Econometrics Journals using Citations Data from ISI and RePEc," Tinbergen Institute Discussion Papers 13-173/III, Tinbergen Institute.
    9. Chia-Lin Chang & Esfandiar Maasoumi & Michael McAleer, 2016. "Robust Ranking of Journal Quality: An Application to Economics," Econometric Reviews, Taylor & Francis Journals, vol. 35(1), pages 50-97, January.
    10. McAleer, M.J., 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Econometric Institute Research Papers EI2015-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Chia-Lin Chang & Michael McAleer, 2013. "What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance," Working Papers in Economics 13/10, University of Canterbury, Department of Economics and Finance.
    12. Juan Miguel Campanario, 2018. "Are leaders really leading? Journals that are first in Web of Science subject categories in the context of their groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 111-130, April.
    13. Chia-Lin Chang & Michael McAleer, 2015. "Bibliometric Rankings of Journals based on the Thomson Reuters Citations Database," Tinbergen Institute Discussion Papers 15-044/III, Tinbergen Institute.
    14. Joseph Gerald Hirschberg & Jeanette Ngaire Lye, 2020. "Grading Journals In Economics: The Abcs Of The Abdc," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 876-921, September.
    15. Chang, C-L. & McAleer, M.J. & Oxley, L., 2012. "Journal Impact Factor, Eigenfactor, Journal Influence and Article Influence," Econometric Institute Research Papers EI 2012-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Chia-Lin Chang & Michael McAleer, 2014. "Quality Weighted Citations Versus Total Citations in the Sciences and Social Sciences," Working Papers in Economics 14/08, University of Canterbury, Department of Economics and Finance.
    17. Haucap, Justus & Muck, Johannes, 2013. "What drives the relevance and reputation of economics journals? An update from a survey among economists," DICE Discussion Papers 103, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    18. Fabio Zagonari, 2019. "Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined," Publications, MDPI, vol. 7(2), pages 1-30, May.
    19. Chang, C-L. & McAleer, M.J., 2015. "Quality Weighted Citations Versus Total Citations in the Sciences and Social Sciences, with an Application to Finance and Accounting," Econometric Institute Research Papers EI 2015-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Chia-Lin Chang & Michael McAleer, 2012. "What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance," Working Papers in Economics 12/02, University of Canterbury, Department of Economics and Finance.
    21. Chia-Lin Chang & Michael McAleer, 2019. "Modeling Latent Carbon Emission Prices for Japan: Theory and Practice," Energies, MDPI, vol. 12(21), pages 1-21, November.
    22. David L. Anderson & John Tressler, 2017. "Researcher rank stability across alternative output measurement schemes in the context of a time limited research evaluation: the New Zealand case," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4542-4553, September.

  43. Franses, Ph.H.B.F. & Mees, H., 2010. "Approximating the DGP of China's Quarterly GDP," Econometric Institute Research Papers EI 2010-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Bataa, Erdenebat & Osborn, Denise R. & Sensier, Marianne, 2018. "China's increasing global influence: Changes in international growth linkages," Economic Modelling, Elsevier, vol. 74(C), pages 194-206.

  44. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," Working Papers in Economics 10/16, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Chang, Chun-Ping & Lee, Chien-Chiang & Hsieh, Meng-Chi, 2015. "Does globalization promote real output? Evidence from quantile cointegration regression," Economic Modelling, Elsevier, vol. 44(C), pages 25-36.
    2. Frankel, Jeffrey, 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Working Paper Series 11-012, Harvard University, John F. Kennedy School of Government.
    3. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    4. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    5. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    6. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2010. "Are Forecast Updates Progressive?," Econometric Institute Research Papers EI 2010-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    8. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Combining Non-Replicable Forecasts," Working Papers in Economics 10/35, University of Canterbury, Department of Economics and Finance.
    9. Jeffrey Frankel, 2011. "A Solution to Fiscal Procyclicality: the Structural Budget Institutions Pioneered by Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 14(2), pages 39-78, August.
    10. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Evaluating Combined Non-Replicable Forecasts," KIER Working Papers 744, Kyoto University, Institute of Economic Research.
    11. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2011. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," KIER Working Papers 771, Kyoto University, Institute of Economic Research.
    12. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    13. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    14. Alexander HARIN, 2014. "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, vol. 2(2), pages 69-79.
    15. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    16. Harin, Alexander, 2014. "General correcting formulae for forecasts," MPRA Paper 55283, University Library of Munich, Germany.

  45. Franses, Ph.H.B.F. & Mees, H., 2010. "Does news on real Chinese GDP growth impact stock markets?," Econometric Institute Research Papers EI 2010-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. , & Hwa, Yen Siew & Chua, Soo Y. & Hooi, Lean Hooi, 2015. "Do Indian Economic Activities Impact ASEAN-5 Stock Markets?," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 49(2), pages 61-76.

  46. Legerstee, R. & Franses, Ph.H.B.F., 2010. "Does Disagreement Amongst Forecasters have Predictive Value?," Econometric Institute Research Papers EI 2010-53, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    2. Franses, Ph.H.B.F. & Welz, M., 2018. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Econometric Institute Research Papers EI2018-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Luiz Félix & Roman Kräussl & Philip Stork, 2021. "Strategic bias and popularity effect in the prediction of economic surprises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1095-1117, September.
    4. Franses, Ph.H.B.F., 2019. "Professional Forecasters and January," Econometric Institute Research Papers EI2019-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    6. Badarinza, Cristian & Gross, Marco, 2011. "Macroeconomic vulnerability and disagreement in expectations," Working Paper Series 1407, European Central Bank.
    7. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Pagenhardt, Laura & Nautz, Dieter & Strohsal, Till, 2015. "The (de-)anchoring of inflation expectations: New evidence from the Euro area," SFB 649 Discussion Papers 2015-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Félix, Luiz & Kräussl, Roman & Stork, Philip, 2018. "Predictable biases in macroeconomic forecasts and their impact across asset classes," CFS Working Paper Series 596, Center for Financial Studies (CFS).

  47. Peers, Y. & Fok, D. & Franses, Ph.H.B.F., 2010. "Modeling Seasonality in New Product Diffusion," ERIM Report Series Research in Management ERS-2010-029-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Xiao, Yu & Han, Jingti, 2016. "Forecasting new product diffusion with agent-based models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 167-178.
    2. Øverby, Harald & Audestad, Jan A. & Szalkowski, Gabriel Andy, 2023. "Compartmental market models in the digital economy—extension of the Bass model to complex economic systems," Telecommunications Policy, Elsevier, vol. 47(1).
    3. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    4. Fernández-Durán, J.J., 2014. "Modeling seasonal effects in the Bass Forecasting Diffusion Model," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 251-264.
    5. Guidolin, Mariangela & Guseo, Renato, 2014. "Modelling seasonality in innovation diffusion," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 33-40.
    6. Collins, Matthew & Curtis, John, 2017. "Advertising and investment spillovers in the diffusion of residential energy efficiency renovations," Papers WP569, Economic and Social Research Institute (ESRI).

  48. van Baardwijk, M. & Franses, Ph.H.B.F., 2010. "The hemline and the economy: is there any match?," Econometric Institute Research Papers EI 2010-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Yabar, J., 2012. "Wait, bond, and buy : Consumer responses to economic crisis," Other publications TiSEM c4298dbe-ef10-433c-91fc-5, Tilburg University, School of Economics and Management.

  49. Kunst, R.M. & Franses, Ph.H.B.F., 2009. "Testing for seasonal unit roots in monthly panels of time series," Econometric Institute Research Papers EI 2009-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Hsu Shih-Hsun, 2021. "Disentangling the source of non-stationarity in a panel of seasonal data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-18, February.
    2. Tiwari, Aviral, 2010. "Is trade deficit sustainable in India? An inquiry," MPRA Paper 24451, University Library of Munich, Germany.
    3. Kunst, Robert M., 2014. "A Combined Nonparametric Test for Seasonal Unit Roots," Economics Series 303, Institute for Advanced Studies.
    4. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.

  50. Roel van Elk & Esther Mot & P.H. Franses, 2009. "Modelling health care expenditures; overview of the literature and evidence from a panel time series model," CPB Discussion Paper 121, CPB Netherlands Bureau for Economic Policy Analysis.

    Cited by:

    1. Kamil Dybczak & Bartosz Przywara, 2010. "The role of technology in health care expenditure in the EU," European Economy - Economic Papers 2008 - 2015 400, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Barkat, Karim & Sbia, Raschid & Maouchi, Youcef, 2019. "Empirical evidence on the long and short run determinants of health expenditure in the Arab world," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 78-87.
    3. Grigorakis, Nikolaos & Floros, Christos & Tsangari, Haritini & Tsoukatos, Evangelos, 2018. "Macroeconomic and financing determinants of out of pocket payments in health care: Evidence from selected OECD countries," Journal of Policy Modeling, Elsevier, vol. 40(6), pages 1290-1312.
    4. Yang, Y., 2014. "Modeling health and mortality dynamics, and their effects on public finance," Other publications TiSEM c0acd15f-e715-46b1-b146-4, Tilburg University, School of Economics and Management.

  51. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2009. "Cointegration in a historical perspective," Econometric Institute Research Papers EI 2009-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    2. Fragiskos Archontakis & Rocco Mosconi, 2021. "Søren Johansen and Katarina Juselius: A Bibliometric Analysis of Citations through Multivariate Bass Models," Econometrics, MDPI, vol. 9(3), pages 1-28, August.

  52. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2009. "How Accurate are Government Forecast of Economic Fundamentals?," Econometric Institute Research Papers EI 2009-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Frankel, Jeffrey, 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Working Paper Series 11-012, Harvard University, John F. Kennedy School of Government.
    2. Jeffrey Frankel, 2011. "A Solution to Fiscal Procyclicality: the Structural Budget Institutions Pioneered by Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 14(2), pages 39-78, August.

  53. Knapp, S. & Franses, Ph.H.B.F., 2009. "Does ratification matter and do major conventions improve safety and decrease pollution in shipping?," Econometric Institute Research Papers EI 2009-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Heij, C. & Bijwaard, G.E. & Knapp, S., 2010. "Ship Inspection Strategies: Effects on Maritime Safety and Environmental Protection," Econometric Institute Research Papers EI 2010-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Vollaard, Ben, 2015. "Temporal Displacement of Environmental Crime : Evidence from Marine Oil Pollution," Other publications TiSEM 6bbaaff7-4d6f-4c9e-987b-f, Tilburg University, School of Economics and Management.
    3. Hristos Karahalios & Z.L. Yang & J. Wang, 2015. "A risk appraisal system regarding the implementation of maritime regulations by a ship operator," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(4), pages 389-413, May.
    4. Emre Akyuz & Hristos Karahalios & Metin Celik, 2015. "Assessment of the maritime labour convention compliance using balanced scorecard and analytic hierarchy process approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(2), pages 145-162, February.
    5. Heij, C. & Knapp, S., 2011. "Risk evaluation methods at individual ship and company level," Econometric Institute Research Papers EI2011-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Karin Reinhold & Marina Järvis & Gunnar Prause, 2019. "Occupational health and safety aspects of green shipping in the Baltic Sea," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(1), pages 10-24, September.
    7. Knapp, S. & van de Velden, M., 2010. "Visualization of Ship Risk Profiles for the Shipping Industry," ERIM Report Series Research in Management ERS-2010-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Hristos Karahalios, 2021. "Contribution of PSC Authorities to Ship Accident Prevention," SN Operations Research Forum, Springer, vol. 2(1), pages 1-18, March.

  54. Franses, Ph.H.B.F. & Segers, R., 2008. "Seasonality in revisions of macroeconomic data," Econometric Institute Research Papers EI 2008-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.

  55. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    2. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2010. "Are Forecast Updates Progressive?," Econometric Institute Research Papers EI 2010-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Combining Non-Replicable Forecasts," Working Papers in Economics 10/35, University of Canterbury, Department of Economics and Finance.
    4. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Evaluating Combined Non-Replicable Forecasts," KIER Working Papers 744, Kyoto University, Institute of Economic Research.
    5. Chia-Lin Chang & Michael McAleer, 2013. "What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance," Working Papers in Economics 13/10, University of Canterbury, Department of Economics and Finance.
    6. Egor Griva & Irina Butorina & Anatoly Sidorov & Pavel Senchenko, 2022. "Analysis and Forecasting of Sales Funnels," Mathematics, MDPI, vol. 11(1), pages 1-22, December.
    7. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    8. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2011. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," KIER Working Papers 771, Kyoto University, Institute of Economic Research.
    9. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    10. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    11. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    12. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Does the ROMC have expertise, and can it forecast?," Econometric Institute Research Papers EI 2008-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Franses, Ph.H.B.F., 2010. "Decomposing bias in expert forecast," Econometric Institute Research Papers EI 2010-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Chia-Lin Chang & Michael McAleer, 2012. "What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance," Working Papers in Economics 12/02, University of Canterbury, Department of Economics and Finance.
    15. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.
    17. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2009. "How Accurate are Government Forecast of Economic Fundamentals?," Econometric Institute Research Papers EI 2009-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  56. Boulaksil, Y. & Franses, Ph.H.B.F., 2008. "Experts' Stated Behavior," ERIM Report Series Research in Management ERS-2008-001-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Boulaksil, Youssef, 2016. "Safety stock placement in supply chains with demand forecast updates," Operations Research Perspectives, Elsevier, vol. 3(C), pages 27-31.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Dellaert, B.G.C. & Arentze, T.A. & Timmermans, H.J.P., 2008. "Shopping Context and Consumers' Mental Representation of Complex Shopping Trip Decision Problems," ERIM Report Series Research in Management ERS-2008-016-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    5. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    6. P H Franses & R Legerstee, 2011. "Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 537-543, March.

  57. van Diepen, M. & Donkers, A.C.D. & Franses, Ph.H.B.F., 2008. "Does Irritation Induced by Charitable Direct Mailings Reduce Donations?," ERIM Report Series Research in Management ERS-2008-036-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Indranil Goswami & Oleg Urminsky, 2016. "When should the ask be a nudge? The Effect of Default Amounts on Charitable Donations," Natural Field Experiments 00659, The Field Experiments Website.
    2. Vesely, Stepan & Klöckner, Christian A. & Carrus, Giuseppe & Chokrai, Parissa & Fritsche, Immo & Masson, Torsten & Panno, Angelo & Tiberio, Lorenza & Udall, Alina M., 2022. "Donations to renewable energy projects: The role of social norms and donor anonymity," Ecological Economics, Elsevier, vol. 193(C).
    3. Tine Hjernø Lesner & Ole Dahl Rasmussen, 2014. "The identifiable victim effect in charitable giving: evidence from a natural field experiment," Applied Economics, Taylor & Francis Journals, vol. 46(36), pages 4409-4430, December.
    4. Ozuna, Edna & Steinhoff, Lena, 2024. "“Look me in the eye, customer”: How do face-to-face interactions in peer-to-peer sharing economy services affect customers’ misbehavior concealment intentions?," Journal of Business Research, Elsevier, vol. 177(C).
    5. Aldashev, Gani & Marini, Marco & Verdier, Thierry, 2014. "Brothers in alms? Coordination between nonprofits on markets for donations," Journal of Public Economics, Elsevier, vol. 117(C), pages 182-200.
    6. Donkers, Bas & van Diepen, Merel & Franses, Philip Hans, 2017. "Do charities get more when they ask more often? Evidence from a unique field experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 66(C), pages 58-65.
    7. van Dijk, Mathilde & Van Herk, Hester & Prins, Remco, 2019. "Choosing your charity: The importance of value congruence in two-stage donation choices," Journal of Business Research, Elsevier, vol. 105(C), pages 283-292.
    8. Gallier, Carlo & Goeschl, Timo & Kesternich, Martin & Lohse, Johannes & Reif, Christiane & Römer, Daniel, 2019. "Inter-charity competition under spatial differentiation: Sorting, crowding, and spillovers," ZEW Discussion Papers 19-039, ZEW - Leibniz Centre for European Economic Research.
    9. Xiaojing Dong & Ramkumar Janakiraman & Ying Xie, 2014. "The Effect of Survey Participation on Consumer Behavior: The Moderating Role of Marketing Communication," Marketing Science, INFORMS, vol. 33(4), pages 567-585, July.
    10. David Fielding & Stephen Knowles, 2013. "Can You Spare Some Change For Charity? Experimental Evidence On Verbal Cues And Loose Change Effects In A Dictator Game," Working Papers 1318, University of Otago, Department of Economics, revised Nov 2013.
    11. Yeomans, Michael & Al-Ubaydli, Omar, 2018. "How does fundraising affect volunteering? Evidence from a natural field experiment," Journal of Economic Psychology, Elsevier, vol. 64(C), pages 57-72.
    12. Ben Grodeck & Philipp Schoenegger, 2022. "Demanding the Morally Demanding: Experimental Evidence on the Effects of Moral Arguments and Moral Demandingness on Charitable Giving," Monash Economics Working Papers 2022-03, Monash University, Department of Economics.
    13. Dorotic, Matilda & Verhoef, Peter C. & Fok, Dennis & Bijmolt, Tammo H.A., 2014. "Reward redemption effects in a loyalty program when customers choose how much and when to redeem," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 339-355.
    14. Jan Schmitz, 2021. "Is Charitable Giving a Zero-Sum Game? The Effect of Competition Between Charities on Giving Behavior," Management Science, INFORMS, vol. 67(10), pages 6333-6349, October.
    15. Reinstein David A, 2011. "Does One Charitable Contribution Come at the Expense of Another?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 11(1), pages 1-54, June.
    16. Krafft, Manfred & Arden, Christine M. & Verhoef, Peter C., 2017. "Permission Marketing and Privacy Concerns — Why Do Customers (Not) Grant Permissions?," Journal of Interactive Marketing, Elsevier, vol. 39(C), pages 39-54.
    17. Elisha Vlaholias & Kirrilly Thompson & Danielle Every & Drew Dawson, 2015. "Charity Starts … at Work? Conceptual Foundations for Research with Businesses that Donate to Food Redistribution Organisations," Sustainability, MDPI, vol. 7(6), pages 1-25, June.
    18. Eckel, Catherine & Guney, Begum & Uler, Neslihan, 2020. "Independent vs. Coordinated Fundraising: Understanding the Role of Information," European Economic Review, Elsevier, vol. 127(C).
    19. Gázquez-Abad, Juan Carlos & Canniére, Marie Hélène De & Martínez-López, Francisco J., 2011. "Dynamics of Customer Response to Promotional and Relational Direct Mailings from an Apparel Retailer: The Moderating Role of Relationship Strength," Journal of Retailing, Elsevier, vol. 87(2), pages 166-181.
    20. Thomas, Suman Ann & Feng, Shanfei & Krishnan, Trichy V., 2015. "To retain? To upgrade? The effects of direct mail on regular donation behavior," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 48-63.
    21. Leeflang, Peter, 2011. "Paving the way for “distinguished marketing”," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 76-88.
    22. Ilya O. Ryzhov & Bin Han & Jelena Bradić, 2016. "Cultivating Disaster Donors Using Data Analytics," Management Science, INFORMS, vol. 62(3), pages 849-866, March.
    23. Jamal, Ahmad & Yaccob, Aqilah & Bartikowski, Boris & Slater, Stephanie, 2019. "Motivations to donate: Exploring the role of religiousness in charitable donations," Journal of Business Research, Elsevier, vol. 103(C), pages 319-327.
    24. Baris K. Yörük, 2009. "Do Fundraisers Select Charitable Donors Based on Gender and Race? Evidence from Survey Data," Discussion Papers 09-01, University at Albany, SUNY, Department of Economics.
    25. George, Morris & Kumar, V. & Grewal, Dhruv, 2013. "Maximizing Profits for a Multi-Category Catalog Retailer," Journal of Retailing, Elsevier, vol. 89(4), pages 374-396.
    26. Choi, Jungsil & Park, Hyun Young, 2021. "How donor's regulatory focus changes the effectiveness of a sadness-evoking charity appeal," International Journal of Research in Marketing, Elsevier, vol. 38(3), pages 749-769.
    27. Feld, Sebastian & Frenzen, Heiko & Krafft, Manfred & Peters, Kay & Verhoef, Peter C., 2013. "The effects of mailing design characteristics on direct mail campaign performance," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 143-159.
    28. Haruvy, Ernan & Popkowski Leszczyc, Peter T.L., 2009. "Bidder motives in cause-related auctions," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 324-331.

  58. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2008. "Incorporating responsiveness to marketing efforts in brand choice modelling," Econometric Institute Research Papers EI 2008-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Kristina Ročkutė & Inga Minelgaitė & Ligita Zailskaitė-Jakštė & Robertas Damaševičius, 2018. "Brand Awareness in the Context of Mistrust: The Case Study of an Employment Agency," Sustainability, MDPI, vol. 10(3), pages 1-13, March.

  59. Henk Kranendonk & Debby Lanser & P.H. Franses, 2007. "On the optimality of expert-adjusted forecasts," CPB Discussion Paper 92, CPB Netherlands Bureau for Economic Policy Analysis.

    Cited by:

    1. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Frank A. G. den Butter & Pieter W. Jansen, 2013. "Beating the random walk: a performance assessment of long-term interest rate forecasts," Applied Financial Economics, Taylor & Francis Journals, vol. 23(9), pages 749-765, May.
    3. Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    4. Kolkman, Daan, 2020. "The usefulness of algorithmic models in policy making," SocArXiv hpma8, Center for Open Science.

  60. Knapp, S. & Franses, Ph.H.B.F., 2007. "Comprehensive review of the maritime safety regimes," Econometric Institute Research Papers EI 2007-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Knapp, Sabine & Franses, Philip Hans, 2009. "Does ratification matter and do major conventions improve safety and decrease pollution in shipping?," Marine Policy, Elsevier, vol. 33(5), pages 826-846, September.
    2. Jelena Nikcevic, 2018. "Montenegro on the Path to Paris MoU Accession: Towards Achieving a Sustainable Shipping Industry," Sustainability, MDPI, vol. 10(6), pages 1-14, June.
    3. Esma Gül Emecen Kara, 2016. "Risk Assessment in the Istanbul Strait Using Black Sea MOU Port State Control Inspections," Sustainability, MDPI, vol. 8(4), pages 1-17, April.
    4. Constantine Chlomoudis & Petros A. Kostagiolas, 2013. "Integrating Information Services for Managing Regulations in International Maritime Transportation," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 63(3-4), pages 128-136, July.

  61. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Ravazzolo, F., 2007. "Evaluating real-time forecasts in real-time," Econometric Institute Research Papers EI 2007-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Clements, Michael P. & Beatriz Galvão, Ana, 2010. "First announcements and real economic activity," European Economic Review, Elsevier, vol. 54(6), pages 803-817, August.

  62. Franses, Ph.H.B.F. & de Groot, E.A. & Legerstee, R., 2007. "Testing for harmonic regressors," Econometric Institute Research Papers EI 2007-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F., 2009. "Testing Changing Harmonic Regressors," Econometric Institute Research Papers EI 2009-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  63. van Dijk, A. & Franses, Ph.H.B.F. & Paap, R. & van Dijk, D.J.C., 2007. "Modeling regional house prices," Econometric Institute Research Papers EI 2007-55, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Andrea Cipollini & Fabio Parla, 2018. "Housing Market Shocks in Italy: a GVAR approach," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0069, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    2. Bing Zhu & Dorinth van Dijk & Colin Lizieri, 2021. "Price diffusion across international private commercial real estate markets," Working Papers 732, DNB.
    3. Ceren Ozgen & Thomas de Graff, 2013. "Sorting out the impact of cultural diversity on innovative firms. An empirical analysis of Dutch micro-data," Norface Discussion Paper Series 2013012, Norface Research Programme on Migration, Department of Economics, University College London.
    4. Holly, Sean & Hashem Pesaran, M. & Yamagata, Takashi, 2011. "The spatial and temporal diffusion of house prices in the UK," Journal of Urban Economics, Elsevier, vol. 69(1), pages 2-23, January.
    5. Dominik Blatt & Kausik Chaudhuri & Hans Manner, 2021. "Spillover in the UK Housing Market," Graz Economics Papers 2021-13, University of Graz, Department of Economics.
    6. James D. Hamilton & Michael T. Owyang, 2009. "The propagation of regional recessions," Working Papers 2009-013, Federal Reserve Bank of St. Louis.
    7. Maureen B.M. Lankhuizen & Thomas de Graaff & Henri L.F. de Groot, 2012. "Product Heterogeneity, Intangible Barriers and Distance Decay: The Effect of Multiple Dimensions of Distance on Trade across Different Product Categories," Tinbergen Institute Discussion Papers 12-065/3, Tinbergen Institute.
    8. Maureen Lankhuizen & Thomas De Graaff & Henri De Groot, 2012. "Product Heterogeneity, Intangible Barriers & Distance Decay: The effect of multiple dimensions of distance on trade across different product categories," ERSA conference papers ersa12p151, European Regional Science Association.
    9. Katharina Pijnenburg, 2017. "The spatial dimension of US house prices," Urban Studies, Urban Studies Journal Limited, vol. 54(2), pages 466-481, February.
    10. Katharina Pijnenburg, 2013. "The Spatial Dimension of US House Price Developments," Discussion Papers of DIW Berlin 1270, DIW Berlin, German Institute for Economic Research.
    11. Ling Zhang & He Wang & Yan Song & Haizhen Wen, 2019. "Spatial Spillover of House Prices: An Empirical Study of the Yangtze Delta Urban Agglomeration in China," Sustainability, MDPI, vol. 11(2), pages 1-17, January.
    12. Osman Dou{g}an & Raffaele Mattera & Philipp Otto & Suleyman Tac{s}p{i}nar, 2024. "A Dynamic Spatiotemporal and Network ARCH Model with Common Factors," Papers 2410.16526, arXiv.org.
    13. Katharina Pijnenburg, 2014. "The Spatial Dimension of US House Price Developments," ERSA conference papers ersa14p127, European Regional Science Association.
    14. Sergei S. Shibaev, 2016. "Recession Propagation In Small Regional Economies: Spatial Spillovers And Endogenous Clustering," Working Paper 1369, Economics Department, Queen's University.
    15. Roel Helgers & Erik Buyst, 2016. "Spatial and Temporal Diffusion of Housing Prices in the Presence of a Linguistic Border: Evidence from Belgium," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(1), pages 92-122, March.

  64. Seger, R. & Franses, Ph.H.B.F., 2007. "Panel design effects on response rates and response quality," Econometric Institute Research Papers EI 2007-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Segers, Rene & Franses, Philip Hans & de Bruijn, Bert, 2017. "A novel approach to measuring consumer confidence," Econometrics and Statistics, Elsevier, vol. 4(C), pages 121-129.
    2. Segers, R. & Franses, Ph.H.B.F., 2008. "Measuring weekly consumer confidence," Econometric Institute Research Papers EI 2008-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  65. Stremersch, S. & Tellis, G.J. & Franses, Ph.H.B.F. & Binken, J.L.G., 2007. "Indirect Network Effects in New Product Growth," ERIM Report Series Research in Management ERS-2007-019-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Maruyama, Masayoshi & Flath, David & Minamikawa, Kazumitsu & Ohkita, Kenichi & Zennyo, Yusuke, 2015. "Platform selection by software developers: Theory and evidence," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 282-303.
    2. Claussen, Jörg & Falck, Oliver & Grohsjean, Thorsten, 2010. "The Strength of Direct Ties: Evidence from the Electronic Game Industry," Discussion Papers in Business Administration 12298, University of Munich, Munich School of Management.
    3. Hallberg, Niklas L. & Brattström, Anna, 2019. "Concealing or revealing? Alternative paths to profiting from innovation," European Management Journal, Elsevier, vol. 37(2), pages 165-174.
    4. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    5. Qi Wang & Huazhong Zhao & Jinhong Xie, 2016. "Intra-Standard Competition: The Joint Impact of an Installed-User Base and a Supporting-Firm Base in Markets with Network Effects," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 159-174, December.
    6. Tim Prostka & Michel Clement & Eva Blömeke & Frank Sambeth, 2011. "Einfluss neuer Technologien auf Angebot und Nachfrage im belletristischen Buchmarkt," Schmalenbach Journal of Business Research, Springer, vol. 63(7), pages 714-744, November.
    7. Gediminas Adomavicius & Jesse Bockstedt & Alok Gupta, 2012. "Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression," Information Systems Research, INFORMS, vol. 23(2), pages 397-417, June.
    8. Ron Adner & Rahul Kapoor, 2016. "Innovation ecosystems and the pace of substitution: Re-examining technology S-curves," Strategic Management Journal, Wiley Blackwell, vol. 37(4), pages 625-648, April.
    9. Narayanan, V.K. & Chen, Tianxu, 2012. "Research on technology standards: Accomplishment and challenges," Research Policy, Elsevier, vol. 41(8), pages 1375-1406.
    10. Kim, Jin-Hyuk & Prince, Jeffrey & Qiu, Calvin, 2014. "Indirect network effects and the quality dimension: A look at the gaming industry," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 99-108.
    11. Leo Van Hove, 2016. "Measuring the value of mobile telecommunications networks," Netnomics, Springer, vol. 17(3), pages 191-222, November.
    12. Garcia-Swartz, Daniel D. & Muhamedagić, Mensur & Saenz, Diana, 2019. "The role of prices and network effects in the growth of the iPhone platform," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 110-122.
    13. Eryn Juan He & Joel Goh, 2022. "Profit or Growth? Dynamic Order Allocation in a Hybrid Workforce," Management Science, INFORMS, vol. 68(8), pages 5891-5906, August.
    14. Jan Frederic Nerbel & Markus Kreutzer, 2023. "Digital platform ecosystems in flux: From proprietary digital platforms to wide-spanning ecosystems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-20, December.
    15. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    16. Bilgicer, Tolga & Jedidi, Kamel & Lehmann, Donald R. & Neslin, Scott A., 2015. "Social Contagion and Customer Adoption of New Sales Channels," Journal of Retailing, Elsevier, vol. 91(2), pages 254-271.
    17. Yutaka Hamaoka, 2009. "Spatial Diffusion of Innovation: A Spatial Panel Analysis of Electronic Toll Collecting Transponders in Japan," Keio/Kyoto Joint Global COE Discussion Paper Series 2009-017, Keio/Kyoto Joint Global COE Program.
    18. Sun, Li & Rajiv, Surendra & Chu, Junhong, 2016. "Beyond the more the merrier: The variety effect and consumer heterogeneity in system markets," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 261-275.
    19. Berg, S. & Wustmans, M. & Bröring, S., 2019. "Identifying first signals of emerging dominance in a technological innovation system: A novel approach based on patents," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 706-722.
    20. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    21. Caner Dincer & Banu Dincer, 2023. "Social Commerce and Purchase Intention: A Brief Look at the Last Decade by Bibliometrics," Sustainability, MDPI, vol. 15(1), pages 1-27, January.
    22. Alina Sorescu & Sorin M. Sorescu & Will J. Armstrong & Bart Devoldere, 2018. "Two Centuries of Innovations and Stock Market Bubbles," Marketing Science, INFORMS, vol. 37(4), pages 507-529, August.
    23. Fabrizio, Kira R. & Hawn, Olga, 2013. "Enabling diffusion: How complementary inputs moderate the response to environmental policy," Research Policy, Elsevier, vol. 42(5), pages 1099-1111.
    24. Seo Eunji & Inoue Yuki, 2023. "Sales effect of a software product series’ length in Japan," Management & Marketing, Sciendo, vol. 18(3), pages 251-269, September.
    25. Antonio Ladrón-de-Guevara & William Putsis, 2015. "Multi-Market, Multi-Product New Product Diffusion: Decomposing Local, Foreign, and Indirect (Cross-Product) Effects," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 57-70, March.
    26. Jie Zhang & Lingfeng Dong & Ting Ji, 2023. "The Diffusion of Competitive Platform-Based Products with Network Effects," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    27. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.
    28. Carlos Córdoba & César García-Díaz, 2020. "Reflexivity in a Diffusion of Innovations Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(3), pages 1-9.
    29. Hess, Thomas & Grau, Christoph & Dörr, Jonathan, 2008. "Download-Angebote für Musik: Hintergründe, Bedeutung und Perspektiven," Working Papers 2/2008, University of Munich, Munich School of Management, Institute for Information Systems and New Media.
    30. Heinz, B. & Graeber, M. & Praktiknjo, A.J., 2013. "The diffusion process of stationary fuel cells in a two-sided market economy," Energy Policy, Elsevier, vol. 61(C), pages 1556-1567.
    31. Wu, Cheng-Han, 2019. "Licensing to a competitor and strategic royalty choice in a dynamic duopoly," European Journal of Operational Research, Elsevier, vol. 279(3), pages 840-853.
    32. Rietveld, G.J. & Eggers, J.P., 2016. "Demand Heterogeneity and the Adoption of Platform Complements," ERIM Report Series Research in Management ERS-2016-003-STR, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    33. Alexei Parakhonyak & Nick Vikander, 2013. "Optimal sales schemes for network goods," HSE Working papers WP BRP 41/EC/2013, National Research University Higher School of Economics.
    34. Garcia-Swartz, Daniel D. & Garcia-Vicente, Florencia, 2015. "Network effects on the iPhone platform: An empirical examination," Telecommunications Policy, Elsevier, vol. 39(10), pages 877-895.
    35. Eunsuk Sung & Hongbum Kim & Daeho Lee, 2018. "Why Do People Consume and Provide Sharing Economy Accommodation?—A Sustainability Perspective," Sustainability, MDPI, vol. 10(6), pages 1-17, June.
    36. Nico Wiegand & Yuri Peers & Alexander Bleier, 2023. "Software multihoming to distal markets: Evidence of cannibalization and complementarity in the video game console industry," Journal of the Academy of Marketing Science, Springer, vol. 51(2), pages 393-417, March.
    37. Yanjie Wu & Sujuan Wang, 2021. "Sustainable Market Entry Strategy under a Supply Chain Environment," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
    38. Angel Sevil & Alfonso Cruz & Tomas Reyes & Roberto Vassolo, 2022. "When Being Large Is Not an Advantage: How Innovation Impacts the Sustainability of Firm Performance in Natural Resource Industries," Sustainability, MDPI, vol. 14(23), pages 1-20, December.
    39. Goldenberg, Jacob & Libai, Barak & Muller, Eitan, 2010. "The chilling effects of network externalities," International Journal of Research in Marketing, Elsevier, vol. 27(1), pages 4-15.
    40. Rodolphe Durand & Robert M. Grant & Tammy L. Madsen & David P. McIntyre & Arati Srinivasan, 2017. "Networks, platforms, and strategy: Emerging views and next steps," Strategic Management Journal, Wiley Blackwell, vol. 38(1), pages 141-160, January.
    41. Stefan Stremersch & Eitan Muller & Renana Peres, 2010. "Does new product growth accelerate across technology generations?," Marketing Letters, Springer, vol. 21(2), pages 103-120, June.
    42. Steiner, Michael & Wiegand, Nico & Eggert, Andreas & Backhaus, Klaus, 2016. "Platform adoption in system markets: The roles of preference heterogeneity and consumer expectations," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 276-296.
    43. Netsanet Haile & Jorn Altmann, 2015. "Value Creation in Software Service Platforms," TEMEP Discussion Papers 2015123, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Sep 2015.
    44. Van Hove, Leo, 2016. "Testing Metcalfe's law: Pitfalls and possibilities," Information Economics and Policy, Elsevier, vol. 37(C), pages 67-76.
    45. Christian Stummer & Dennis Kundisch & Reinhold Decker, 2018. "Platform Launch Strategies," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 60(2), pages 167-173, April.
    46. Emanuele Giovannetti & Mohsen Hamoudia, 2022. "The interaction between direct and indirect network externalities in the early diffusion of mobile social networking," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 617-642, December.
    47. Richard T. Gretz & Ashwin Malshe & Carlos Bauer & Suman Basuroy, 2019. "The impact of superstar and non-superstar software on hardware sales: the moderating role of hardware lifecycle," Journal of the Academy of Marketing Science, Springer, vol. 47(3), pages 394-416, May.
    48. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    49. Joost Rietveld & J. P. Eggers, 2018. "Demand Heterogeneity in Platform Markets: Implications for Complementors," Organization Science, INFORMS, vol. 29(2), pages 304-322, April.
    50. Kevin J. Boudreau & Lars Bo Jeppesen & Milan Miric, 2022. "Competing on freemium: Digital competition with network effects," Strategic Management Journal, Wiley Blackwell, vol. 43(7), pages 1374-1401, July.
    51. Böger, Maximilian & Wecht, Christoph H. & Stalder, Céline, 2019. "Hybrid Business Platforms – Marketplaces of the Future," Marketing Review St.Gallen, Universität St.Gallen, Institut für Marketing und Customer Insight, vol. 36(2), pages 38-44.
    52. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    53. Maxime C. Cohen & Pavithra Harsha, 2020. "Designing Price Incentives in a Network with Social Interactions," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 292-309, March.
    54. Matta, Vic & Koonce, David & Jeyaraj, Anand, 2012. "Initiation, Experimentation, Implementation of innovations: The case for Radio Frequency Identification Systems," International Journal of Information Management, Elsevier, vol. 32(2), pages 164-174.
    55. Marchand, André & Hennig-Thurau, Thorsten, 2013. "Value Creation in the Video Game Industry: Industry Economics, Consumer Benefits, and Research Opportunities," Journal of Interactive Marketing, Elsevier, vol. 27(3), pages 141-157.
    56. Prins, Remco & Verhoef, Peter C. & Franses, Philip Hans, 2009. "The impact of adoption timing on new service usage and early disadoption," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 304-313.

  66. Franses, Ph.H.B.F. & Legerstee, R., 2007. "Does experts' adjustment to model-based forecasts contribute to forecast quality?," Econometric Institute Research Papers EI 2007-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    2. Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    3. A A Syntetos & N C Georgantzas & J E Boylan & B C Dangerfield, 2011. "Judgement and supply chain dynamics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1138-1158, June.

  67. Mariëlle C. Non & Philip Hans Franses, 2007. "Interlocking Boards and Firm Performance: Evidence from a New Panel Database," Tinbergen Institute Discussion Papers 07-034/2, Tinbergen Institute.

    Cited by:

    1. Mazzola, Erica & Perrone, Giovanni & Kamuriwo, Dzidziso Samuel, 2016. "The interaction between inter-firm and interlocking directorate networks on firm's new product development outcomes," Journal of Business Research, Elsevier, vol. 69(2), pages 672-682.
    2. Carlos Drago & Francesco Millo & Roberto Ricciuti & Paolo Santella, 2011. "Corporate Governance Reforms, Interlocking Directorship Networks and Company Value in Italy (1998-2007)," CESifo Working Paper Series 3322, CESifo.
    3. Tao, Qizhi & Li, Haoyu & Wu, Qun & Zhang, Ting & Zhu, Yingjun, 2019. "The dark side of board network centrality: Evidence from merger performance," Journal of Business Research, Elsevier, vol. 104(C), pages 215-232.
    4. Drago, Carlo & Millo, Francesco & Ricciuti, Roberto & Santella, Paolo, 2014. "Corporate Governance Reforms, Interlocking Directorship and Company Performance in Italy," MPRA Paper 59217, University Library of Munich, Germany.
    5. Battistin, Erich & Graziano, Clara & Parigi, Bruno M., 2012. "Connections and performance in bankers’ turnover," European Economic Review, Elsevier, vol. 56(3), pages 470-487.
    6. Larcker, David F. & So, Eric C. & Wang, Charles C.Y., 2013. "Boardroom centrality and firm performance," Journal of Accounting and Economics, Elsevier, vol. 55(2), pages 225-250.
    7. Remzi Gözübüyük & Carl Joachim Kock & Murat Ünal, 2020. "Who appropriates centrality rents? The role of institutions in regulating social networks in the global Islamic finance industry," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(5), pages 764-787, July.
    8. Tetsuji Okazaki & Michiru Sawada, 2012. "Interbank networks in prewar Japan: structure and implications," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 21(2), pages 463-506, April.
    9. Leonardo BECCHETTI & Fabio PISANI, 2015. "The Determinants of Outreach Performance of Social Business: an Inquiry on Italian Social Cooperatives," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 86(1), pages 105-136, March.
    10. Ettore Croci & Rosanna Grassi, 2014. "The economic effect of interlocking directorates in Italy: new evidence using centrality measures," Computational and Mathematical Organization Theory, Springer, vol. 20(1), pages 89-112, March.
    11. Larcker, David F. & So, Eric C. & Wang, Charles C. Y., 2010. "Boardroom Centrality and Stock Returns," Research Papers 2061, Stanford University, Graduate School of Business.
    12. Lucia Bellenzier & Rosanna Grassi, 2014. "Interlocking directorates in Italy: persistent links in network dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 183-202, October.

  68. van Diepen, M. & Donkers, A.C.D. & Franses, Ph.H.B.F., 2006. "Irritation Due to Direct Mailings from Charities," ERIM Report Series Research in Management ERS-2006-029-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Meer, Jonathan & Rosen, Harvey S., 2011. "The ABCs of charitable solicitation," Journal of Public Economics, Elsevier, vol. 95(5), pages 363-371.
    2. Jonathan Meer & Harvey S. Rosen, 2008. "The ABCs of Charitable Solicitation," Working Papers 1057, Princeton University, Department of Economics, Center for Economic Policy Studies..
    3. van Bruggen, G.H. & Spann, M. & Lilien, G.L. & Skiera, B., 2006. "Institutional Forecasting: The Performance of Thin Virtual Stock Markets," ERIM Report Series Research in Management ERS-2006-028-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Reinstein, David, 2006. "Does One Contribution Come at the Expense of Another? Empirical Evidence on Substitution Between Charitable Donations," Economics Discussion Papers 2938, University of Essex, Department of Economics.

  69. Knapp, S. & Franses, Ph.H.B.F., 2006. "Analysis of the Maritime Inspection Regimes - Are ships over-inspected?," Econometric Institute Research Papers EI 2006-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Panagiotis Sotiralis & Konstantinos Louzis & Nikolaos P Ventikos, 2019. "The role of ship inspections in maritime accidents: An analysis of risk using the bow-tie approach," Journal of Risk and Reliability, , vol. 233(1), pages 58-70, February.

  70. Ravazzolo, F. & van Dijk, D.J.C. & Paap, R. & Franses, Ph.H.B.F., 2006. "Bayesian Model Averaging in the Presence of Structural Breaks," Econometric Institute Research Papers EI 2006-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Guidolin, Massimo & Ravazzolo, Francesco & Tortora, Andrea Donato, 2013. "Alternative econometric implementations of multi-factor models of the U.S. financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(2), pages 87-111.
    3. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    4. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    6. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    7. Massimo Guidolin & Francesco Ravazzolo & Andrea Tortora, 2014. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 49(4), pages 477-523, November.
    8. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
    9. Massimo Guidolin & Francesco Ravazzolo & Andrea Donato Tortora, 2011. "Myths and facts about the alleged over-pricing of U.S. real estate. Evidence from multi-factor asset pricing models of REIT returns," Working Paper 2011/19, Norges Bank.
    10. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    11. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    12. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Ravazzolo, F., 2007. "Evaluating real-time forecasts in real-time," Econometric Institute Research Papers EI 2007-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.

  71. van Nierop, J.E.M. & Fok, D. & Franses, Ph.H.B.F., 2006. "Interaction Between Shelf Layout and Marketing Effectiveness and Its Impact On Optimizing Shelf Arrangements," ERIM Report Series Research in Management ERS-2006-013-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Sergio Meza & K. Sudhir, 2010. "Do private labels increase retailer bargaining power?," Quantitative Marketing and Economics (QME), Springer, vol. 8(3), pages 333-363, September.
    2. Schäfer, Fabian & Hense, Jonas & Hübner, Alexander, 2023. "An analytical assessment of demand effects in omni-channel assortment planning," Omega, Elsevier, vol. 115(C).
    3. Péter Boros & Orsolya Fehér & Zoltán Lakner & Sadegh Niroomand & Béla Vizvári, 2016. "Modeling supermarket re-layout from the owner’s perspective," Annals of Operations Research, Springer, vol. 238(1), pages 27-40, March.
    4. Grewal, Dhruv & Levy, Michael & Kumar, V., 2009. "Customer Experience Management in Retailing: An Organizing Framework," Journal of Retailing, Elsevier, vol. 85(1), pages 1-14.
    5. Constant Berkhout & Abhi Bhattacharya & Carlos Bauer & Ross W. Johnson, 2024. "Revisiting the construct of data-driven decision making: antecedents, scope, and boundaries," SN Business & Economics, Springer, vol. 4(10), pages 1-23, October.
    6. Mantrala, Murali K. & Levy, Michael & Kahn, Barbara E. & Fox, Edward J. & Gaidarev, Peter & Dankworth, Bill & Shah, Denish, 2009. "Why is Assortment Planning so Difficult for Retailers? A Framework and Research Agenda," Journal of Retailing, Elsevier, vol. 85(1), pages 71-83.
    7. Heydari Majeed & Yousefli Amir, 2017. "A new optimization model for market basket analysis with allocation considerations: A genetic algorithm solution approach," Management & Marketing, Sciendo, vol. 12(1), pages 1-11, March.
    8. Hense, Jonas & Hübner, Alexander, 2022. "Assortment optimization in omni-channel retailing," European Journal of Operational Research, Elsevier, vol. 301(1), pages 124-140.
    9. Hübner, Alexander & Schaal, Kai, 2017. "A shelf-space optimization model when demand is stochastic and space-elastic," Omega, Elsevier, vol. 68(C), pages 139-154.
    10. van Nierop, J.E.M. & Leeflang, P.S.H. & Teerling, M.L. & Huizingh, K.R.E., 2011. "The impact of the introduction and use of an informational website on offline customer buying behavior," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 155-165.
    11. Kateryna Czerniachowska, 2022. "A genetic algorithm for the retail shelf space allocation problem with virtual segments," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 364-412, March.
    12. Meyer, Jan-Hinrich & González, Eva M. & Lopez-Lomelí, Miguel A., 2022. "Better support for supportive jobs. How to improve brand performance through better compensation and training for in-store merchandisers," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    13. van Everdingen, Yvonne M. & Sloot, Laurens M. & van Nierop, Erjen & Verhoef, Peter C., 2011. "Towards a Further Understanding of the Antecedents of Retailer New Product Adoption," Journal of Retailing, Elsevier, vol. 87(4), pages 579-597.
    14. Hunneman, Auke & Bijmolt, Tammo H.A. & Elhorst, J. Paul, 2023. "Evaluating store location and department composition based on spatial heterogeneity in sales potential," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    15. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    16. Roose, Gudrun & Vermeir, Iris, 2023. "Putting spatial product presentation cues on the map: Review and research directions," Journal of Business Research, Elsevier, vol. 155(PA).
    17. Erica Herpen & Erjen Nierop & Laurens Sloot, 2012. "The relationship between in-store marketing and observed sales for organic versus fair trade products," Marketing Letters, Springer, vol. 23(1), pages 293-308, March.
    18. Yu Tian & Sebastian Lautz & Alisdiar O. G. Wallis & Renaud Lambiotte, 2021. "Extracting Complements and Substitutes from Sales Data: A Network Perspective," Papers 2103.02042, arXiv.org, revised Aug 2021.
    19. Aaron Staples & Bridget K. Behe & Patricia Huddleston & Trey Malone, 2022. "What you see is what you get, and what you don't goes unsold: Choice overload and purchasing heuristics in a horticulture lab experiment," Agribusiness, John Wiley & Sons, Ltd., vol. 38(3), pages 620-635, July.
    20. Bianchi-Aguiar, Teresa & Hübner, Alexander & Carravilla, Maria Antónia & Oliveira, José Fernando, 2021. "Retail shelf space planning problems: A comprehensive review and classification framework," European Journal of Operational Research, Elsevier, vol. 289(1), pages 1-16.
    21. Caglar Gencosman, Burcu & Begen, Mehmet A., 2022. "Exact optimization and decomposition approaches for shelf space allocation," European Journal of Operational Research, Elsevier, vol. 299(2), pages 432-447.
    22. Zhao, Ju & Zhou, Yong-Wu & Wahab, M.I.M., 2016. "Joint optimization models for shelf display and inventory control considering the impact of spatial relationship on demand," European Journal of Operational Research, Elsevier, vol. 255(3), pages 797-808.
    23. Gecili, Hakan & Parikh, Pratik J., 2022. "Joint shelf design and shelf space allocation problem for retailers," Omega, Elsevier, vol. 111(C).
    24. van Bruggen, G.H. & Spann, M. & Lilien, G.L. & Skiera, B., 2006. "Institutional Forecasting: The Performance of Thin Virtual Stock Markets," ERIM Report Series Research in Management ERS-2006-028-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    25. Bauer, Johannes C. & Kotouc, Alexander J. & Rudolph, Thomas, 2012. "What constitutes a “good assortment†? A scale for measuring consumers' perceptions of an assortment offered in a grocery category," Journal of Retailing and Consumer Services, Elsevier, vol. 19(1), pages 11-26.
    26. Pizzi, Gabriele & Scarpi, Daniele, 2016. "The effect of shelf layout on satisfaction and perceived assortment size: An empirical assessment," Journal of Retailing and Consumer Services, Elsevier, vol. 28(C), pages 67-77.
    27. Adam, Abdulfatah & Jensen, Jørgen D. & Sommer, Iben & Hansen, Gitte L., 2017. "Does shelf space management intervention have an effect on calorie turnover at supermarkets?," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 311-318.
    28. Gabriele Pizzi & Gian Luca Marzocchi, 2020. "Consumer-defined assortments: application of card-sorting to category management," Italian Journal of Marketing, Springer, vol. 2020(1), pages 67-84, March.
    29. Torik Holmes & Josi Fernandes & Teea Palo, 2021. "‘Spatio-market practices’: conceptualising the always spatial dimensions of market making practices," AMS Review, Springer;Academy of Marketing Science, vol. 11(3), pages 316-335, December.
    30. Péter Boros & Orsolya Fehér & Zoltán Lakner & Sadegh Niroomand & Béla Vizvári, 2016. "Modeling supermarket re-layout from the owner’s perspective," Annals of Operations Research, Springer, vol. 238(1), pages 27-40, March.
    31. Robert P. Rooderkerk & Harald J. van Heerde & Tammo H. A. Bijmolt, 2013. "Optimizing Retail Assortments," Marketing Science, INFORMS, vol. 32(5), pages 699-715, September.

  72. Rotger, G.P. & Franses, Ph.H.B.F., 2006. "Forecasting high-frequency electricity demand with a diffusion index model," Econometric Institute Research Papers EI 2006-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Mestekemper, Thomas & Kauermann, Göran & Smith, Michael S., 2013. "A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting," International Journal of Forecasting, Elsevier, vol. 29(1), pages 1-12.

  73. van Diepen, M. & Donkers, A.C.D. & Franses, Ph.H.B.F., 2006. "Dynamic and Competitive Effects of Direct Mailings," ERIM Report Series Research in Management ERS-2006-050-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Gani Aldashev & Thierry Verdier, 2010. "Goodwill bazaar: NGO competition and giving to development," PSE-Ecole d'économie de Paris (Postprint) halshs-00754487, HAL.
    2. Meer, Jonathan & Rosen, Harvey S., 2011. "The ABCs of charitable solicitation," Journal of Public Economics, Elsevier, vol. 95(5), pages 363-371.
    3. David Fielding & Stephen Knowles, 2013. "Can You Spare Some Change For Charity? Experimental Evidence On Verbal Cues And Loose Change Effects In A Dictator Game," Working Papers 1318, University of Otago, Department of Economics, revised Nov 2013.
    4. Jonathan Meer & Harvey S. Rosen, 2008. "The ABCs of Charitable Solicitation," Working Papers 1057, Princeton University, Department of Economics, Center for Economic Policy Studies..
    5. Zeynep B. Ugur, 2018. "Donate More, Be Happier! Evidence from the Netherlands," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 13(1), pages 157-177, March.
    6. Ugur, Z.B., 2013. "From headscarves to donation : Three essays on the economics of gender, health and happiness," Other publications TiSEM 9cfb068c-c08e-47aa-8c44-f, Tilburg University, School of Economics and Management.

  74. Dekimpe, M.G. & Franses, Ph.H.B.F. & Hanssens, D.M. & Naik, P., 2006. "Time-Series Models in Marketing," ERIM Report Series Research in Management ERS-2006-049-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Sa-ngasoongsong, Akkarapol & Bukkapatnam, Satish T.S. & Kim, Jaebeom & Iyer, Parameshwaran S. & Suresh, R.P., 2012. "Multi-step sales forecasting in automotive industry based on structural relationship identification," International Journal of Production Economics, Elsevier, vol. 140(2), pages 875-887.
    2. Long Gao & Birendra K. Mishra, 2019. "The Role of Market Evolution in Channel Contracting," Management Science, INFORMS, vol. 67(5), pages 2432-2441, May.
    3. Sandy D. Jap & Prasad A. Naik, 2008. "BidAnalyzer: A Method for Estimation and Selection of Dynamic Bidding Models," Marketing Science, INFORMS, vol. 27(6), pages 949-960, 11-12.

  75. Franses, Ph.H.B.F. & van Oest, R.D., 2006. "Testing changes in consumer confidence indicators," Econometric Institute Research Papers EI 2006-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Maurizio Bovi, 2008. "The “Psycho-analysis” of Common People’s Forecast Errors. Evidence from European Consumer Surveys," ISAE Working Papers 95 Classification-JEL C42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

  76. H.P. Boswijk & D. Fok & P.-H. Franses, 2006. "A New Multivariate Product Growth Model," Tinbergen Institute Discussion Papers 06-027/4, Tinbergen Institute.

    Cited by:

    1. Torben Klarl, 2014. "Knowledge diffusion and knowledge transfer revisited: two sides of the medal," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 737-760, September.

  77. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2005. "Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results," Econometric Institute Research Papers EI 2005-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Christian Gayer & Julien Genet, 2006. "Using factor models to construct composite indicators from BCS data - a comparison with European Commission confidence indicators," European Economy - Economic Papers 2008 - 2015 240, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Bhattacharya, Rina, 2014. "Inflation dynamics and monetary policy transmission in Vietnam and emerging Asia," Journal of Asian Economics, Elsevier, vol. 34(C), pages 16-26.
    3. Luciana Crosilla, 2006. "The seasonality of ISAE business and consumer surveys: methodological aspects and empirical evidence," ISAE Working Papers 68, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    4. Barend Abeln & Jan P.A.M. Jacobs, 2015. "Seasonal adjustment with and without revisions: A comparison of X-13ARIMA-SEATS and CAMPLET," CAMA Working Papers 2015-25, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Beria, Paolo & Laurino, Antonio, 2016. "Determinants of daily fluctuations in air passenger volumes. The effect of events and holidays on Milan Malpensa airport," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 73-84.
    6. Inna S. Lola, 2017. "The Statistical Measurement of Business Conditions for Small Entrepreneurs," HSE Working papers WP BRP 71/STI/2017, National Research University Higher School of Economics.

  78. van Nierop, J.E.M. & Paap, R. & Bronnenberg, B. & Franses, Ph.H.B.F. & Wedel, M., 2005. "Retrieving unobserved consideration sets from household panel data," Econometric Institute Research Papers EI 2005-49, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Joseph Pancras, 2010. "A Framework to Determine the Value of Consumer Consideration Set Information for Firm Pricing Strategies," Computational Economics, Springer;Society for Computational Economics, vol. 35(3), pages 269-300, March.
    2. Wuyts, S.H.K. & Verhoef, P. & Prins, R., 2009. "Partner selection in B2B informational service markets," Other publications TiSEM 35b4b91f-294c-47a6-95b2-7, Tilburg University, School of Economics and Management.
    3. Stephan Seiler, 2010. "The impact of search costs on consumer behavior: a dynamic approach," 2010 Meeting Papers 559, Society for Economic Dynamics.
    4. Steven M. Shugan, 2006. "Editorial: Errors in the Variables, Unobserved Heterogeneity, and Other Ways of Hiding Statistical Error," Marketing Science, INFORMS, vol. 25(3), pages 203-216, 05-06.
    5. Wuyts, Stefan & Verhoef, Peter C. & Prins, Remco, 2009. "Partner selection in B2B information service markets," International Journal of Research in Marketing, Elsevier, vol. 26(1), pages 41-51.

  79. Fok, D. & Franses, Ph.H.B.F., 2005. "Seasonality on non-linear price effects in scanner-data based market-response models," Econometric Institute Research Papers EI 2005-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Peers, Y. & Fok, D. & Franses, Ph.H.B.F., 2010. "Modeling Seasonality in New Product Diffusion," ERIM Report Series Research in Management ERS-2010-029-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Wolters, Jannik & Huchzermeier, Arnd, 2021. "Joint In-Season and Out-of-Season Promotion Demand Forecasting in a Retail Environment," Journal of Retailing, Elsevier, vol. 97(4), pages 726-745.
    3. Qi Feng & Sirong Luo & Dan Zhang, 2014. "Dynamic Inventory–Pricing Control Under Backorder: Demand Estimation and Policy Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 149-160, February.
    4. Venera Timiryanova & Irina Lakman & Vadim Prudnikov & Dina Krasnoselskaya, 2022. "Spatial Dependence of Average Prices for Product Categories and Its Change over Time: Evidence from Daily Data," Forecasting, MDPI, vol. 5(1), pages 1-25, December.
    5. Guidolin, Mariangela & Guseo, Renato, 2014. "Modelling seasonality in innovation diffusion," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 33-40.
    6. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
    7. Haupt, Harry & Kagerer, Kathrin, 2012. "Beyond mean estimates of price and promotional effects in scanner-panel sales–response regression," Journal of Retailing and Consumer Services, Elsevier, vol. 19(5), pages 470-483.

  80. Fok, D. & Franses, Ph.H.B.F., 2005. "Modeling the diffusion of scientific publications," Econometric Institute Research Papers EI 2005-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Marc Fischer & Peter Leeflang & Peter Verhoef, 2010. "Drivers of peak sales for pharmaceutical brands," Quantitative Marketing and Economics (QME), Springer, vol. 8(4), pages 429-460, December.
    2. David I. Stern, 2017. "Comment on Bornmann (2017): confidence intervals for journal impact factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1811-1813, December.
    3. Lutz Bornmann & Adam Y. Ye & Fred Y. Ye, 2018. "Identifying “hot papers” and papers with “delayed recognition” in large-scale datasets by using dynamically normalized citation impact scores," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 655-674, August.
    4. Gelper, Sarah & Stremersch, Stefan, 2014. "Variable selection in international diffusion models," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 356-367.
    5. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2009. "Cointegration in a historical perspective," Econometric Institute Research Papers EI 2009-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. R. G. Raj & A. N. Zainab, 2012. "Relative measure index: a metric to measure the quality of journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 305-317, November.
    7. Jinyoung Kim & Kanghyock Koh, 2014. "Incentives for Journal Editors," Canadian Journal of Economics, Canadian Economics Association, vol. 47(1), pages 348-371, February.
    8. Michael Schymura & Andreas Löschel, 2014. "Incidence and extent of co-authorship in environmental and resource economics: evidence from the Journal of Environmental Economics and Management," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 631-661, June.
    9. Richard S. J. Tol, 2011. "Credit where credit’s due: accounting for co-authorship in citation counts," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 291-299, October.
    10. Yi-Tui Chen & Fu-Chiang Yang & Shih-Heng Yu, 2017. "The Diffusion Effect of MSW Recycling," Sustainability, MDPI, vol. 10(1), pages 1-12, December.
    11. Erjen Van Nierop, 2009. "Why do statistics journals have low impact factors?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 52-62, February.
    12. Giovanni Modanese, 2023. "The Network Bass Model with Behavioral Compartments," Stats, MDPI, vol. 6(2), pages 1-13, March.
    13. Teodora Diana Corsatea, 2010. "Measuring science: Spatial investigation of academic opportunities in Belgium," Papers in Regional Science, Wiley Blackwell, vol. 89(2), pages 373-387, June.
    14. García-Suaza, Andrés & Otero, Jesus & Winkelmann, Rainer, 2018. "Early Career Research Production in Economics: Does Mentoring Matter?," IZA Discussion Papers 11976, Institute of Labor Economics (IZA).
    15. Howlett, Peter, 2008. "Travelling in the social science community: assessing the impact of the Indian Green Revolution across disciplines," Economic History Working Papers 22513, London School of Economics and Political Science, Department of Economic History.
    16. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Zeki Simsek & Ciaran Heavey & Justin J. P. Jansen, 2013. "Journal Impact as a Diffusion Process: A Conceptualization and the Case of the Journal of Management Studies," Journal of Management Studies, Wiley Blackwell, vol. 50(8), pages 1374-1407, December.
    18. Bornmann, Lutz & Leydesdorff, Loet, 2017. "Skewness of citation impact data and covariates of citation distributions: A large-scale empirical analysis based on Web of Science data," Journal of Informetrics, Elsevier, vol. 11(1), pages 164-175.
    19. Bornmann, Lutz, 2019. "Does the normalized citation impact of universities profit from certain properties of their published documents – such as the number of authors and the impact factor of the publishing journals? A mult," Journal of Informetrics, Elsevier, vol. 13(1), pages 170-184.
    20. Bornmann, Lutz & Tekles, Alexander, 2021. "Convergent validity of several indicators measuring disruptiveness with milestone assignments to physics papers by experts," Journal of Informetrics, Elsevier, vol. 15(3).
    21. Hou, Jianhua & Li, Hao & Zhang, Yang, 2024. "Influence of interdisciplinarity of scientific papers on the durability of citation diffusion: A perspective from citation discontinuance," Journal of Informetrics, Elsevier, vol. 18(3).
    22. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.

  81. Hafner, C.M. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2005. "Semi-Parametric Modelling of Correlation Dynamics," Econometric Institute Research Papers EI 2005-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH model," SSE/EFI Working Paper Series in Economics and Finance 0652, Stockholm School of Economics.
    3. Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Multivariate GARCH models," CREATES Research Papers 2008-06, Department of Economics and Business Economics, Aarhus University.
    4. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    5. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    6. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    7. Wasel Shadat & Chris Orme, 2011. "An investigation of parametric tests of CCC assumption," Economics Discussion Paper Series 1109, Economics, The University of Manchester.

  82. de Groot, E.A. & Franses, Ph.H.B.F., 2005. "Real time estimates of GDP growth, based on two-regime models," Econometric Institute Research Papers EI 2005-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. den Reijer, Ard H.J., 2011. "Regional and sectoral dynamics of the Dutch staffing labor cycle," Economic Modelling, Elsevier, vol. 28(4), pages 1826-1837, July.

  83. de Groot, E.A. & Franses, Ph.H.B.F., 2005. "Real time estimates of GDP growth," Econometric Institute Research Papers EI 2005-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F. & de Groot, E.A., 2006. "Long-term forecast for the Dutch economy," Econometric Institute Research Papers EI 2006-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Elke J. Jahn & Jan Bentzen, 2012. "What Drives the Demand for Temporary Agency Workers?," LABOUR, CEIS, vol. 26(3), pages 341-355, September.
    3. de Groot, E.A. & Franses, Ph.H.B.F., 2005. "Real time estimates of GDP growth, based on two-regime models," Econometric Institute Research Papers EI 2005-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. den Reijer, Ard H.J., 2011. "Regional and sectoral dynamics of the Dutch staffing labor cycle," Economic Modelling, Elsevier, vol. 28(4), pages 1826-1837, July.
    5. Philip Hans Franses, 2011. "Model selection for forecast combination," Applied Economics, Taylor & Francis Journals, vol. 43(14), pages 1721-1727.
    6. ten Cate, Arie & Franses, Philip Hans, 2008. "Error-correction modelling in discrete and continuous time," Economics Letters, Elsevier, vol. 101(2), pages 140-141, November.

  84. Franses, Ph.H.B.F. & Paap, R., 2005. "Random-Coefficient periodic autoregression," Econometric Institute Research Papers EI 2005-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Aknouche, Abdelhakim & Guerbyenne, Hafida, 2009. "Periodic stationarity of random coefficient periodic autoregressions," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 990-996, April.
    2. Aknouche, Abdelhakim & Rabehi, Nadia, 2024. "Inspecting a seasonal ARIMA model with a random period," MPRA Paper 120758, University Library of Munich, Germany.
    3. Dennis Fok & Philip Hans Franses, 2013. "Testing earnings management," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(3), pages 281-292, August.
    4. KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Business and Economics.
    5. Paul L. Anderson & Farzad Sabzikar & Mark M. Meerschaert, 2021. "Parsimonious time series modeling for high frequency climate data," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 442-470, July.
    6. Kiygi Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2012. "The effectiveness of high-frequency direct-response commercials," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 98-109.
    7. Aknouche, Abdelhakim & Al-Eid, Eid & Demouche, Nacer, 2016. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," MPRA Paper 75770, University Library of Munich, Germany, revised 19 Dec 2016.
    8. Abdelhakim Aknouche & Eid Al-Eid & Nacer Demouche, 2018. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 485-511, October.

  85. de Groot, E.A. & Franses, Ph.H.B.F., 2005. "Cycles in basic innovations," Econometric Institute Research Papers EI 2005-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. de Groot, E.A. & Franses, Ph.H.B.F., 2006. "Stability through cycles," Econometric Institute Research Papers EI 2006-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Tan, Hao & Mathews, John A., 2010. "Identification and analysis of industry cycles," Journal of Business Research, Elsevier, vol. 63(5), pages 454-462, May.
    3. Hao Tan & John A. Mathews, 2007. "Cyclical Dynamics in Three Industries," DRUID Working Papers 07-07, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.

  86. Bruyneel, S. & Dewitte, S. & Franses, Ph.H.B.F. & Dekimpe, M.G., 2005. "Why Consumers Buy Lottery Tickets When the Sun Goes Down on Them. The Depleting Nature of Weather-Induced Bad Moods," ERIM Report Series Research in Management ERS-2005-045-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Martijn (M.J.) Burger & Martijn Hendriks & Emma Pleeging & Jan (J.C.) van Ours, 2018. "The Joy of Lottery Play: Evidence from a Field Experiment," Tinbergen Institute Discussion Papers 18-078/V, Tinbergen Institute.

  87. Fok, D. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2004. "Forecasting aggregates using panels of nonlinear time series," Econometric Institute Research Papers EI 2004-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Kausik Chaudhuri & Saumitra N. Bhaduri, 2019. "Inflation Forecast: Just use the Disaggregate or Combine it with the Aggregate," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 331-343, June.
    2. Cai, Charlie X. & Kyaw, Khine & Zhang, Qi, 2012. "Stock index return forecasting: The information of the constituents," Economics Letters, Elsevier, vol. 116(1), pages 72-74.
    3. Oliveira, André Barbosa & Valls Pereira, Pedro Luiz, 2018. "Asset Allocation with Markovian Regime Switching: Efficient Frontier and Tangent Portfolio with Regime Switching," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
    4. Oliveira, André Barbosa & Pereira, Pedro L. Valls, 2018. "Uncertainty times for portfolio selection at financial market," Textos para discussão 473, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    5. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    6. Nina Vujanovic & Bruno Casella & Richard Bolwijn, . "Forecasting global FDI: a panel data approach," UNCTAD Transnational Corporations Journal, United Nations Conference on Trade and Development.
    7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    8. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    9. Allenby, Greg M., 2017. "Structural forecasts for marketing data," International Journal of Forecasting, Elsevier, vol. 33(2), pages 433-441.
    10. Baltagi, Badi H., 2006. "Forecasting with panel data," Discussion Paper Series 1: Economic Studies 2006,25, Deutsche Bundesbank.
    11. Chang, Tsangyao & Chiang, Gengnan, 2012. "Transitional Behavior of Government Debt Ratio on Growth: The Case of OECD Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 24-37, June.

  88. Franses, Ph.H.B.F. & Vriens, M., 2004. "Advertising effects on awareness, consideration and brand choice using tracking data," ERIM Report Series Research in Management ERS-2004-028-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Elisabeth Honka & Ali Hortaçsu & Maria Ana Vitorino, 2017. "Advertising, consumer awareness, and choice: evidence from the U.S. banking industry," RAND Journal of Economics, RAND Corporation, vol. 48(3), pages 611-646, August.
    2. Dominique M. Hanssens & Koen H. Pauwels & Shuba Srinivasan & Marc Vanhuele & Gokhan Yildirim, 2014. "Consumer Attitude Metrics for Guiding Marketing Mix Decisions," Marketing Science, INFORMS, vol. 33(4), pages 534-550, July.

  89. Sándor, Z. & Franses, Ph.H.B.F., 2004. "Experimental investigation of consumer price evaluations," Econometric Institute Research Papers EI 2004-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Hu, Wuyang, 2006. "Effects of Endogenous Task Complexity and the Endowed Bundle on Stated Choice," 2006 Annual meeting, July 23-26, Long Beach, CA 21437, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

  90. Fok, D. & Horváth, C. & Paap, R. & Franses, Ph.H.B.F., 2004. "A hierarchical Bayes error correction model to explain dynamic effects," Econometric Institute Research Papers EI 2004-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Vroegrijk, Mark & Gijsbrechts, Els & Campo, Katia, 2016. "Battling for the Household's Category Buck: Can Economy Private Labels Defend Supermarkets Against the Hard-Discounter Threat?," Journal of Retailing, Elsevier, vol. 92(3), pages 300-318.
    2. van Heerde, H.J. & Helsen, K. & Dekimpe, M.G., 2005. "Managing Product-Harm Crises," ERIM Report Series Research in Management ERS-2005-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. van Everdingen, Y.M. & Fok, D. & Stremersch, S., 2008. "Modeling Global Spill-Over of New Product Takeoff," ERIM Report Series Research in Management ERS-2008-067-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Dawes, John G., 2012. "Brand-Pack Size Cannibalization Arising from Temporary Price Promotions," Journal of Retailing, Elsevier, vol. 88(3), pages 343-355.
    5. Frison, Steffi & Dekimpe, Marnik G. & Croux, Christophe & De Maeyer, Peter, 2014. "Billboard and cinema advertising: Missed opportunity or spoiled arms?," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 425-433.
    6. KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Business and Economics.
    7. van Heerde, H.J. & Dekimpe, M.G. & Putsis, W.P., 2004. "Marketing Models and the Lucas Critique," ERIM Report Series Research in Management ERS-2004-080-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.

  91. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Patricia Chelley-Steeley & James Steeley, 2005. "The leverage effect in the UK stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 15(6), pages 409-423.
    2. Appel, Gil & Libai, Barak & Muller, Eitan, 2018. "On the monetary impact of fashion design piracy," International Journal of Research in Marketing, Elsevier, vol. 35(4), pages 591-610.
    3. Pauwels, Koen & Neslin, Scott A., 2015. "Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment," Journal of Retailing, Elsevier, vol. 91(2), pages 182-197.
    4. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.
    5. Alexander Faehnle & Mariangela Guidolin, 2021. "Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes," Forecasting, MDPI, vol. 3(1), pages 1-15, March.
    6. Rafael Barreiros Porto & Nolah Schutte da Rocha Lima, 2015. "Nonlinear Impact of the Marketing Mix on Brand Sales Performance," Brazilian Business Review, Fucape Business School, vol. 12(5), pages 57-77, September.

  92. Franses, Ph.H.B.F. & van Oest, R.D., 2004. "On the econometrics of the Koyck model," Econometric Institute Research Papers EI 2004-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Melvin Woodley, 2021. "Decoupling the individual effects of multiple marketing channels with state space models," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 248-255, June.
    3. Nicolae-Marius JULA, 2015. "Modelling loans and deposits during electoral years in Romania," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 3(1), pages 43-48, June.
    4. Vighneswara Swamy, 2022. "Financial wealth effects and consumption expenditure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1933-1946, April.
    5. Alexandra Horobet & Georgiana Vrinceanu & Consuela Popescu & Lucian Belascu, 2019. "Oil Price and Stock Prices of EU Financial Companies: Evidence from Panel Data Modeling," Energies, MDPI, vol. 12(21), pages 1-17, October.
    6. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    7. Philip Hans Franses, 2004. "Fifty years since Koyck (1954)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 381-387, November.

  93. P.H. Franses & D. Fok & D. van Dijk, 2004. "A Multi-Level Panel Smooth Transition Autoregression for US Sectoral Production," Econometric Society 2004 Australasian Meetings 267, Econometric Society.

    Cited by:

    1. Oleg Korenok & Bruce Mizrach & Stan Radchenko, 2004. "The Microeconomics of Macroeconomic Asymmetries: Sectoral Driving Forces and Firm Level Characteristics," Departmental Working Papers 200405, Rutgers University, Department of Economics.
    2. Po-Chin Wu & Chung-Chih Lee, 2018. "The non-linear impact of monetary policy on international reserves: macroeconomic variables nexus," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 165-185, February.
    3. Xiaoping He & Xin Yao, 2017. "Foreign Direct Investments and the Environmental Kuznets Curve: New Evidence from Chinese Provinces," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(1), pages 12-25, January.

  94. Bijwaard, G.E. & Franses, Ph.H.B.F. & Paap, R., 2003. "Modeling purchases as repeated events," Econometric Institute Research Papers EI 2003-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Nishio, Kazuki & Hoshino, Takahiro, 2022. "Joint modeling of effects of customer tier program on customer purchase duration and purchase amount," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    2. Andros Kourtellos & Charalambos G. Tsangarides, 2015. "Robust Correlates of Growth Spells: Do Inequality and Redistribution Matter?," Working Paper series 15-20, Rimini Centre for Economic Analysis.
    3. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    4. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Govert Bijwaard, 2012. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," Norface Discussion Paper Series 2012033, Norface Research Programme on Migration, Department of Economics, University College London.
    6. Zhuoxin Li & Jason A. Duan & Sam Ransbotham, 2020. "Coordination and Dynamic Promotion Strategies in Crowdfunding with Network Externalities," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 1032-1049, April.
    7. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    8. Bijwaard, G.E., 2005. "Regularity in individual shopping trips: Implications for duration models in marketing," Econometric Institute Research Papers EI 2005-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.
    10. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.
    11. Lawrence Kryzanowski & Yanting Wu, 2023. "Signaling effects of recurrent list‐price reductions on the likelihood of house sales," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 99-130, February.
    12. Zhuoxin Li & Jason A. Duan, 2014. "Dynamic Strategies for Successful Online Crowdfunding," Working Papers 14-09, NET Institute.
    13. Lizhen Xu & Jason A. Duan & Andrew Whinston, 2014. "Path to Purchase: A Mutually Exciting Point Process Model for Online Advertising and Conversion," Management Science, INFORMS, vol. 60(6), pages 1392-1412, June.
    14. Govert Ewout Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.

  95. Franses, Ph.H.B.F. & Vroomen, B.L.K., 2003. "Estimating duration intervals," ERIM Report Series Research in Management ERS-2003-031-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  96. Franses, Ph.H.B.F., 2003. "Do we make better forecasts these days? A survey amongst academics," Econometric Institute Research Papers EI 2003-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Philip Hans Franses, 2004. "Do We Think We Make Better Forecasts Than in the Past? A Survey of Academics," Interfaces, INFORMS, vol. 34(6), pages 466-468, December.

  97. Horváth, C. & Franses, Ph.H.B.F., 2003. "Deriving dynamic marketing effectiveness from econometric time series models," ERIM Report Series Research in Management ERS-2003-079-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Sismeiro, Catarina & Mizik, Natalie & Bucklin, Randolph E., 2012. "Modeling coexisting business scenarios with time-series panel data: A dynamics-based segmentation approach," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 134-147.

  98. Rodrigues, P.M.M. & Franses, Ph.H.B.F., 2003. "A sequential approach to testing seasonal unit roots in high frequency data," Econometric Institute Research Papers EI 2003-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Okrent, Abigail M. & Alston, Julian M., 2010. "The Demand for Food in the United States: A Review of the Literature, Evaluation of Previous Estimates, and Presentation of New Estimates of Demand," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61674, Agricultural and Applied Economics Association.
    2. Martinez-Espineira, Roberto, 2005. "An Estimation of Residential Water Demand Using Co-Integration and Error Correction Techniques," MPRA Paper 615, University Library of Munich, Germany, revised Jan 2006.
    3. Jani Beko & Timotej Jagric, 2009. "Demand models for direct mail and periodicals delivery services: results for a transition economy," Applied Economics, Taylor & Francis Journals, vol. 43(9), pages 1125-1138.
    4. Ridderstaat, Jorge & Oduber, Marck & Croes, Robertico & Nijkamp, Peter & Martens, Pim, 2014. "Impacts of seasonal patterns of climate on recurrent fluctuations in tourism demand: Evidence from Aruba," Tourism Management, Elsevier, vol. 41(C), pages 245-256.
    5. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
    6. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    7. Andres Silva & Senarath Dharmasena, 2016. "Considering seasonal unit root in a demand system: an empirical approach," Empirical Economics, Springer, vol. 51(4), pages 1443-1463, December.

  99. Pauwels, K.H. & Franses, Ph.H.B.F. & Srinivasan, S., 2003. "Reference-based transitions in short-run price elasticity," ERIM Report Series Research in Management ERS-2003-095-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Timothy J. Richards & Miguel I. Gómez & Iryna Printezis, 2016. "Hysteresis, Price Acceptance, and Reference Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 679-706.
    2. Boztuğ, Yasemin & Hildebrandt, Lutz, 2005. "An empirical test of theories of price valuation using a semiparametric approach, reference prices, and accounting for heterogeneity," SFB 649 Discussion Papers 2005-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  100. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Dennis Karstanje & Elvira Sojli & Wing Wah Tham & Michel van der Wel, 2013. "Economic Valuation of Liquidity Timing," Tinbergen Institute Discussion Papers 13-156/IV/DSF64, Tinbergen Institute.
    3. Dunz, Nepomuk & Naqvi, Asjad & Monasterolo, Irene, 2019. "Climate Transition Risk, Climate Sentiments, and Financial Stability in a Stock-Flow Consistent approach," Ecological Economic Papers 23, WU Vienna University of Economics and Business.
    4. Luca Brugnolini & Antonello D’Agostino & Alex Tagliabracci, 2021. "Is Anything Predictable in Market-Based Surprises?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 7(3), pages 387-410, November.
    5. Salas-Molina, Francisco & Martin, Francisco J. & Rodríguez-Aguilar, Juan A. & Serrà, Joan & Arcos, Josep Ll., 2017. "Empowering cash managers to achieve cost savings by improving predictive accuracy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 403-415.
    6. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    7. Yavuz, Nilgün Çil & Yilanci, Veli, 2012. "Testing For Nonlinearity In G7 Macroeconomic Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 69-79, September.
    8. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    9. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
    10. Zapart, Christopher A., 2009. "On entropy, financial markets and minority games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1157-1172.
    11. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
    12. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    13. Sznajderska, Anna, 2013. "On the empirical evidence of asymmetric effects in the Polish interest rate pass-through," The Journal of Economic Asymmetries, Elsevier, vol. 10(2), pages 78-93.
    14. Michal Franta, 2016. "The Effect of Nonlinearity between Credit Conditions and Economic Activity on Density Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 147-166, March.
    15. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
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    17. Kauppi, Heikki & Virtanen, Timo, 2021. "Boosting nonlinear predictability of macroeconomic time series," International Journal of Forecasting, Elsevier, vol. 37(1), pages 151-170.
    18. Nikolay Robinzonov & Gerhard Tutz & Torsten Hothorn, 2012. "Boosting techniques for nonlinear time series models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 99-122, January.
    19. Diteboho Xaba & Ntebogang Dinah Moroke & Ishmael Rapoo, 2019. "Modeling Stock Market Returns of BRICS with a Markov-Switching Dynamic Regression Model," Journal of Economics and Behavioral Studies, AMH International, vol. 11(3), pages 10-22.
    20. Kasai, Ndahiriwe & Naraidoo, Ruthira, 2011. "Evaluating the forecasting performance of linear and nonlinear monetary policy rules for South Africa," MPRA Paper 40699, University Library of Munich, Germany.
    21. Patrick T. Kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2016. "Forecasting South African inflation using non-linearmodels: a weighted loss-based evaluation," Applied Economics, Taylor & Francis Journals, vol. 48(26), pages 2412-2427, June.
    22. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    23. Nava, Noemi & Di Matteo, Tiziana & Aste, Tomaso, 2018. "Financial time series forecasting using empirical mode decomposition and support vector regression," LSE Research Online Documents on Economics 91028, London School of Economics and Political Science, LSE Library.
    24. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
    25. Costanza Torricelli & Marianna Brunetti, 2006. "Economic activity and Recession Probabilities: spread predictive power in Italy," Computing in Economics and Finance 2006 350, Society for Computational Economics.
    26. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
    27. Noemi Nava & Tiziana Di Matteo & Tomaso Aste, 2018. "Financial Time Series Forecasting Using Empirical Mode Decomposition and Support Vector Regression," Risks, MDPI, vol. 6(1), pages 1-21, February.
    28. Francisco Salas-Molina & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Montserrat Guillen & Francisco J. Martin, 2016. "Empirical analysis of daily cash flow time series and its implications for forecasting," Papers 1611.04941, arXiv.org, revised Jun 2017.
    29. Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
    30. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    31. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    32. Marie Bessec & Othman Bouabdallah, 2005. "What causes the forecasting failure of Markov-Switching models? A Monte Carlo study," Econometrics 0503018, University Library of Munich, Germany.
    33. Martha Cecilia García & Aura María Jalal & Luis Alfonso Garzón & Jorge Mario López, 2013. "Métodos para predecir índices Bursátiles," Revista Ecos de Economía, Universidad EAFIT, December.
    34. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    35. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
    36. Hamza, Taher & Ben Haj Hamida, Hayet & Mili, Mehdi & Sami, Mina, 2024. "High inflation during Russia–Ukraine war and financial market interaction: Evidence from C-Vine Copula and SETAR models," Research in International Business and Finance, Elsevier, vol. 70(PB).
    37. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    38. Zeeshan Ahmad & Shudi Bao & Meng Chen, 2024. "DeepONet-Inspired Architecture for Efficient Financial Time Series Prediction," Mathematics, MDPI, vol. 12(24), pages 1-27, December.
    39. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    40. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    41. Dat Thanh Tran & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2021. "Bilinear Input Normalization for Neural Networks in Financial Forecasting," Papers 2109.00983, arXiv.org.
    42. Zaher Mundher Yaseen & Mazen Ismaeel Ghareb & Isa Ebtehaj & Hossein Bonakdari & Ridwan Siddique & Salim Heddam & Ali A. Yusif & Ravinesh Deo, 2018. "Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 105-122, January.
    43. Yueling Xu & Wenyu Zhang & Haijun Bao & Shuai Zhang & Ying Xiang, 2019. "A SEM–Neural Network Approach to Predict Customers’ Intention to Purchase Battery Electric Vehicles in China’s Zhejiang Province," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    44. Dunz, Nepomuk & Naqvi, Asjad & Monasterolo, Irene, 2021. "Climate sentiments, transition risk, and financial stability in a stock-flow consistent model," Journal of Financial Stability, Elsevier, vol. 54(C).
    45. Emrah Önder & Ali Hepşen, 2013. "Combining Time Series Analysis and Multi Criteria Decision Making Techniques for Forecasting Financial Performance of Banks in Turkey," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 3(3), pages 530-530.
    46. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.
    47. Zuzanna Karolak, 2021. "Energy prices forecasting using nonlinear univariate models," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 577-598.
    48. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    49. Heikki Kauppi & Timo Virtanen, 2018. "Boosting Non-linear Predictabilityof Macroeconomic Time Series," Discussion Papers 124, Aboa Centre for Economics.
    50. Ahmad Alsharef & Sonia & Karan Kumar & Celestine Iwendi, 2022. "Time Series Data Modeling Using Advanced Machine Learning and AutoML," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    51. Henri Nyberg, 2018. "Forecasting US interest rates and business cycle with a nonlinear regime switching VAR model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(1), pages 1-15, January.
    52. Jiang, He & Tao, Changqi & Dong, Yao & Xiong, Ren, 2021. "Robust low-rank multiple kernel learning with compound regularization," European Journal of Operational Research, Elsevier, vol. 295(2), pages 634-647.
    53. Michael P. Clements & David F. Hendry, 2005. "Guest Editors’ Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
    54. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    55. Kuosmanen, Petri & Nabulsi, Nasib & Vataja, Juuso, 2015. "Financial variables and economic activity in the Nordic countries," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 368-379.
    56. Li, Dandan & Ghoshray, Atanu & Morley, Bruce, 2013. "An empirical study of nonlinear adjustment in the UIP model using a smooth transition regression model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 109-120.
    57. He, Kaijian & Xu, Yang & Zou, Yingchao & Tang, Ling, 2015. "Electricity price forecasts using a Curvelet denoising based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 1-9.
    58. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    59. David Alan Peel & Pantelis Promponas, 2016. "Forecasting the nominal exchange rate movements in a changing world. The case of the U.S. and the U.K," Working Papers 144439514, Lancaster University Management School, Economics Department.
    60. Kaijian He & Rui Zha & Jun Wu & Kin Keung Lai, 2016. "Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price," Sustainability, MDPI, vol. 8(4), pages 1-11, April.

  101. Kippers, J. & Franses, Ph.H.B.F., 2003. "An empirical analysis of euro cash payments," Econometric Institute Research Papers EI 2003-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Bouhdaoui, Y. & Bounie, D. & François, A., 2014. "Convenient prices, cash payments and price rigidity," Economic Modelling, Elsevier, vol. 41(C), pages 329-337.
    2. Bruno Karoubi & R駩s Chenavaz, 2015. "Prices for cash and cash for prices? Theory and evidence on convenient pricing," Applied Economics, Taylor & Francis Journals, vol. 47(38), pages 4102-4115, August.
    3. Régis Chenavaz & Joeffrey Drouard & Octavio R. Escobar & Bruno Karoubi, 2018. "Convenience pricing in online retailing: Evidence from Amazon.com," Post-Print halshs-01683838, HAL.
    4. Joshi Harit & Mukherjee, Saral, 2017. "Transitions in currency denomination structure as supply disruption and demand distortion: Efficiency, Effectiveness and Bullwhip," IIMA Working Papers WP 2017-05-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    5. Prescott, Brian C. & Shy, Oz, 2023. "Cash payments and the penny policy debate," Journal of Economic Behavior & Organization, Elsevier, vol. 208(C), pages 80-94.
    6. Bouhdaoui, Yassine & Van Hove, Leo, 2017. "On the socially optimal density of coin and banknote series: Do production costs really matter?," Journal of Macroeconomics, Elsevier, vol. 52(C), pages 252-267.
    7. Carlos A. Arango A. & Martha Misas A. & Juan Nicolás Hernández, 2004. "La Demanda de Especies Monetarias en Colombia: Estructura y Pronóstico," Borradores de Economia 309, Banco de la Republica de Colombia.
    8. Adriaan R. Soetevent, 2011. "Payment Choice, Image Motivation and Contributions to Charity: Evidence from a Field Experiment," American Economic Journal: Economic Policy, American Economic Association, vol. 3(1), pages 180-205, February.
    9. Philip Hans Franses, 2006. "On modeling panels of time series," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(4), pages 438-456, November.
    10. Bouhdaoui, Y. & Bounie, D., 2012. "Efficient payments: How much do they cost for the Central Bank?," Economic Modelling, Elsevier, vol. 29(5), pages 1579-1584.
    11. Franses, Ph.H.B.F. & Kippers, J., 2003. "How do we pay with euro notes? Empirical evidence from Monopoly experiments," Econometric Institute Research Papers EI 2003-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Philip Hans Franses & Max Welz, 2019. "Cash Use of the Taiwan Dollar: Is It Efficient? †," JRFM, MDPI, vol. 12(1), pages 1-6, January.
    13. Bouhdaoui, Y. & Bounie, D. & Van Hove, L., 2011. "Central banks and their banknote series: The efficiency-cost trade-off," Economic Modelling, Elsevier, vol. 28(4), pages 1482-1488, July.

  102. Hafner, C.M. & Franses, Ph.H.B.F., 2003. "A generalized dynamic conditional correlation model for many asset returns," Econometric Institute Research Papers EI 2003-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. C S Savva & D R Osborn & L Gill, 2005. "Spillovers and Correlations between US and Major European Stock Markets: The Role of the Euro," Economics Discussion Paper Series 0515, Economics, The University of Manchester.
    2. Ray Chou & Chun-Chou Wu & Nathan Liu, 2009. "Forecasting time-varying covariance with a range-based dynamic conditional correlation model," Review of Quantitative Finance and Accounting, Springer, vol. 33(4), pages 327-345, November.
    3. Christodoulakis, George A., 2007. "Common volatility and correlation clustering in asset returns," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1263-1284, November.
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    5. Jin Guo & Tetsuji Tanaka, 2020. "Examining the determinants of global and local price passthrough in cereal markets: evidence from DCC-GJR-GARCH and panel analyses," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 8(1), pages 1-22, December.
    6. Christian M. Hafner & Dick van Dijk & Philip Hans Franses, 2006. "Semi-Parametric Modelling of Correlation Dynamics," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 59-103, Emerald Group Publishing Limited.
    7. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    8. Amine Lahiani & Khaled Guesmi, 2014. "Commodity Price Correlation and Time varying Hedge Ratios," Working Papers 2014-142, Department of Research, Ipag Business School.
    9. Christos Savva & Denise R Osborn & Len Gill, 2005. "Volatility, spillover Effects and Correlations in US and Major European Markets," Money Macro and Finance (MMF) Research Group Conference 2005 23, Money Macro and Finance Research Group.
    10. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.
    11. Samitas, Aristeidis & Tsakalos, Ioannis, 2013. "How can a small country affect the European economy? The Greek contagion phenomenon," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 18-32.
    12. Kosater, Peter, 2006. "Cross-city hedging with weather derivatives using bivariate DCC GARCH models," Discussion Papers in Econometrics and Statistics 2/06, University of Cologne, Institute of Econometrics and Statistics.
    13. Li, Leon, 2017. "Dynamic correlations and domestic-global diversification," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 280-290.
    14. Dick van Dijk & Haris Munandar & Christian Hafner, 2011. "The euro introduction and noneuro currencies," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 95-116.
    15. Giulio Palomba, 2008. "Multivariate GARCH models and the Black-Litterman approach for tracking error constrained portfolios: an empirical analysis," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 379-413.
    16. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    17. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Practical volatility and correlation modeling for financial market risk management," CFS Working Paper Series 2005/02, Center for Financial Studies (CFS).
    18. Sukriye Tuysuz, 2012. "How have the Turkish post-2001 stabilization reforms impacted on the conditional correlation between the Turkish and the main foreign stock markets?," Applied Financial Economics, Taylor & Francis Journals, vol. 22(22), pages 1881-1898, November.
    19. Monica Billio & Massimiliano Caporin, 2006. "A generalized Dynamic Conditional Correlation Model for Portfolio Risk Evaluation," Working Papers 2006_53, Department of Economics, University of Venice "Ca' Foscari".
    20. Vargas, Gregorio A., 2008. "What Drives the Dynamic Conditional Correlation of Foreign Exchange and Equity Returns?," MPRA Paper 7174, University Library of Munich, Germany.
    21. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    22. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  103. Paap, R. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 2003. "Does Africa grow slower than Asia and Latin America?," Econometric Institute Research Papers EI 2003-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Fok, D. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2003. "A multi-level panel smooth transition autoregression for US sectoral production," Econometric Institute Research Papers EI 2003-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    3. Grinis, Inna, 2017. "Trend growth durations & shifts," LSE Research Online Documents on Economics 85126, London School of Economics and Political Science, LSE Library.

  104. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2003. "Modeling Dynamic Effects of the Marketing Mix on Market Shares," ERIM Report Series Research in Management ERS-2003-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Frison, Steffi & Dekimpe, Marnik G. & Croux, Christophe & De Maeyer, Peter, 2014. "Billboard and cinema advertising: Missed opportunity or spoiled arms?," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 425-433.
    2. Ma, Shaohui & Fildes, Robert, 2017. "A retail store SKU promotions optimization model for category multi-period profit maximization," European Journal of Operational Research, Elsevier, vol. 260(2), pages 680-692.
    3. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.

  105. van Dijk, D.J.C. & Franses, Ph.H.B.F., 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Econometric Institute Research Papers EI 2003-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Avino, Davide & Nneji, Ogonna, 2012. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," MPRA Paper 42848, University Library of Munich, Germany.
    2. Mehmet Balcilar & NICO KATZKE & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 15-05, Eastern Mediterranean University, Department of Economics.
    3. Aye, Goodness C. & Balcilar, Mehmet & Gupta, Rangan & Majumdar, Anandamayee, 2015. "Forecasting aggregate retail sales: The case of South Africa," International Journal of Production Economics, Elsevier, vol. 160(C), pages 66-79.
    4. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    5. Tatevik Sekhposyan & Barbara Rossi, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    6. Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2014. "The Role of Economic Policy Uncertainty in Forecasting US Inflation Using a VARFIMA Model," Working Papers 15-12, Eastern Mediterranean University, Department of Economics.
    7. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. Jean-michel Sahut & Medhi Mili & Frédéric Teulon, 2012. "What is the linkage between real growth in the Euro area and global financial market conditions?," Economics Bulletin, AccessEcon, vol. 32(3), pages 2464-2480.
    9. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    10. Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
    11. Goodness C. Aye & Mehmet Balcilar & Adél Bosch & Rangan Gupta & Francois Stofberg, 2013. "The out-of-sample forecasting performance of non-linear models of real exchange rate behaviour: The case of the South African Rand," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 10(1), pages 121-148, April.
    12. Costas Milas & Ruthira Naraidoo, 2009. "Financial Market Conditions, Real Time, Nonlinearity and European Central Bank Monetary Policy: In-Sample and Out-of-Sample Assessment," Working Paper series 42_09, Rimini Centre for Economic Analysis.
    13. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
    14. Balcilar, Mehmet & Gupta, Rangan & van Eyden, Reneé & Thompson, Kirsten & Majumdar, Anandamayee, 2018. "Comparing the forecasting ability of financial conditions indices: The case of South Africa," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 245-259.
    15. Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2011. "Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production," Munich Reprints in Economics 19953, University of Munich, Department of Economics.
    16. George Athanasopoulos & Rob J Hyndman & Raffaele Mattera, 2023. "Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering," Monash Econometrics and Business Statistics Working Papers 17/23, Monash University, Department of Econometrics and Business Statistics.
    17. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
    18. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 785-794.
    19. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    20. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working papers 2012-38, University of Connecticut, Department of Economics, revised Dec 2013.
    21. Florackis, Chris & Giorgioni, Gianluigi & Kostakis, Alexandros & Milas, Costas, 2014. "On stock market illiquidity and real-time GDP growth," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 210-229.
    22. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    23. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
    24. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    25. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
    26. James Engel & David Haugh & Adrian Pagan, 2004. "Some methods for assessing the need for non-linear models in business cycle analysis," CAMA Working Papers 2004-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    27. Milas, Costas & Naraidoo, Ruthira, 2012. "Financial conditions and nonlinearities in the European Central Bank (ECB) reaction function: In-sample and out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 173-189, January.
    28. Mili, Mehdi & Sahut, Jean-Michel & Teulon, Frédéric, 2012. "Non linear and asymmetric linkages between real growth in the Euro area and global financial market conditions: New evidence," Economic Modelling, Elsevier, vol. 29(3), pages 734-741.
    29. Cerqueti, Roy & Ficcadenti, Valerio & Mattera, Raffaele, 2024. "Investors’ attention and network spillover for commodity market forecasting," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).

  106. Kippers, J. & Franses, Ph.H.B.F., 2003. "Do we need all Euro denominations?," Econometric Institute Research Papers EI 2003-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F. & Kippers, J., 2003. "How do we pay with euro notes? Empirical evidence from Monopoly experiments," Econometric Institute Research Papers EI 2003-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  107. van Oest, R.D. & Franses, Ph.H.B.F., 2003. "Which brands gain share from which brands? Inference from store-level scanner data," ERIM Report Series Research in Management ERS-2003-076-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Eric Anderson & Nanda Kumar, 2007. "Price competition with repeat, loyal buyers," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 333-359, December.
    2. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.

  108. Koning, A.J. & Franses, Ph.H.B.F., 2003. "Confidence Intervals for Cronbach's Coefficient Alpha Values," ERIM Report Series Research in Management ERS-2003-041-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Samson Okello & Benson Nasasira & Anthony Ndichu Wa Muiru & Anthony Muyingo, 2016. "Validity and Reliability of a Self-Reported Measure of Antihypertensive Medication Adherence in Uganda," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-11, July.
    2. Arana-Solares, Iván Andrés & Ortega-Jiménez, César H. & Alfalla-Luque, Rafaela & Pérez-Díez de los Ríos, José Luis, 2019. "Contextual factors intervening in the manufacturing strategy and technology management-performance relationship," International Journal of Production Economics, Elsevier, vol. 207(C), pages 81-95.
    3. Leontitsis, Alexandros & Pagge, Jenny, 2007. "A simulation approach on Cronbach's alpha statistical significance," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 73(5), pages 336-340.

  109. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2002. "A simple test for PPP among traded goods," Econometric Institute Research Papers EI 2002-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Hong, Seung Hyun & Phillips, Peter C. B., 2010. "Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 96-114.
    2. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.

  110. Dekker, D.J. & Krackhardt, D. & Franses, Ph.H.B.F., 2002. "Dynamic Effects of Trust and Cognitive Social Structures on Information Transfer Relationships," ERIM Report Series Research in Management ERS-2002-33-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Adam M. Kleinbaum & Alexander H. Jordan & Pino G. Audia, 2015. "An Altercentric Perspective on the Origins of Brokerage in Social Networks: How Perceived Empathy Moderates the Self-Monitoring Effect," Organization Science, INFORMS, vol. 26(4), pages 1226-1242, August.

  111. Boswijk, H.P. & Franses, Ph.H.B.F., 2002. "The Econometrics Of The Bass Diffusion Model," ERIM Report Series Research in Management ERS-2002-66-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Marc Fischer & Peter Leeflang & Peter Verhoef, 2010. "Drivers of peak sales for pharmaceutical brands," Quantitative Marketing and Economics (QME), Springer, vol. 8(4), pages 429-460, December.
    2. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    3. Torben Klarl, 2014. "Knowledge diffusion and knowledge transfer revisited: two sides of the medal," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 737-760, September.
    4. Franses, Ph.H.B.F. & Hernández-Mireles, C., 2006. "When Should Nintendo Launch its Wii? Insights From a Bivariate Successive Generation Model," ERIM Report Series Research in Management ERS-2006-032-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Jonathan Beck, 2006. "The Sales Effect of Word of Mouth: A Model for Creative Goods and Estimates for Novels," CIG Working Papers SP II 2006-16, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
    6. Beck, Jonathan, 2009. "Diderot's rule," MPRA Paper 17404, University Library of Munich, Germany.
    7. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2009. "Cointegration in a historical perspective," Econometric Institute Research Papers EI 2009-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Jacob Goldenberg & Oded Lowengart & Daniel Shapira, 2009. "Zooming In: Self-Emergence of Movements in New Product Growth," Marketing Science, INFORMS, vol. 28(2), pages 274-292, 03-04.
    10. Chihyun Jung & Dae-Eun Lim, 2016. "Development of an Adaptive Forecasting System: A Case Study of a PC Manufacturer in South Korea," Sustainability, MDPI, vol. 8(3), pages 1-12, March.
    11. Peers, Y. & Fok, D. & Franses, Ph.H.B.F., 2010. "Modeling Seasonality in New Product Diffusion," ERIM Report Series Research in Management ERS-2010-029-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Fok, D. & Franses, Ph.H.B.F., 2005. "Modeling the diffusion of scientific publications," Econometric Institute Research Papers EI 2005-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Fragiskos Archontakis & Rocco Mosconi, 2021. "Søren Johansen and Katarina Juselius: A Bibliometric Analysis of Citations through Multivariate Bass Models," Econometrics, MDPI, vol. 9(3), pages 1-28, August.
    14. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    15. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
    16. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    17. Franses, Ph.H.B.F., 2003. "On the Bass diffusion theory, empirical models and out-of-sample forecasting," ERIM Report Series Research in Management ERS-2003-034-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. Shiva & Neetu Gupta & Anu G. Aggarwal, 2024. "A generalized product adoption model under random marketing conditions," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(10), pages 4897-4904, October.
    19. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Klarl, Torben, 2009. "Knowledge diffusion and knowledge transfer: two sides of the medal," ZEW Discussion Papers 09-080, ZEW - Leibniz Centre for European Economic Research.
    21. Claudia Furlan & Cinzia Mortarino & Mohammad Salim Zahangir, 2021. "Interaction among three substitute products: an extended innovation diffusion model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 269-293, March.
    22. Hong, Jungsik & Koo, Hoonyoung & Kim, Taegu, 2016. "Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS," European Journal of Operational Research, Elsevier, vol. 248(2), pages 681-690.
    23. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    24. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    25. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    26. Fernández-Durán, J.J., 2014. "Modeling seasonal effects in the Bass Forecasting Diffusion Model," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 251-264.
    27. Claudia Furlan & Cinzia Mortarino, 2020. "Comparison among simultaneous confidence regions for nonlinear diffusion models," Computational Statistics, Springer, vol. 35(4), pages 1951-1991, December.
    28. International Monetary Fund, 2005. "Mauritius: Selected Issues and Statistical Appendix," IMF Staff Country Reports 2005/280, International Monetary Fund.
    29. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    30. H.P. Boswijk & D. Fok & P.-H. Franses, 2006. "A New Multivariate Product Growth Model," Tinbergen Institute Discussion Papers 06-027/4, Tinbergen Institute.

  112. Jonker, J.-J. & Franses, Ph.H.B.F. & Piersma, N., 2002. "Evaluating Direct Marketing Campaigns: recent findings and future research topics," ERIM Report Series Research in Management ERS-2002-26-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Todor Krastevich, 2013. "Using Predictive Modeling to Improve Direct Marketing Performance," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 25-55.

  113. Franses, Ph.H.B.F. & Verhoef, P.C., 2002. "On combining revealed and stated preferences to forecast customer behaviour: three case studies," Econometric Institute Research Papers EI 2002-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Reynolds, Travis & Kolodinsky, Jane & Murray, Byron, 2012. "Consumer preferences and willingness to pay for compact fluorescent lighting: Policy implications for energy efficiency promotion in Saint Lucia," Energy Policy, Elsevier, vol. 41(C), pages 712-722.
    2. Gitto, Lara, 2021. "L’offerta di beni culturali in Sicilia: analisi econometrica dei flussi turistici negli anni 1999 e 2000 [Cultural heritage in Sicily: econometric analysis of tourist flows in the years 1999 and 20," MPRA Paper 105309, University Library of Munich, Germany.
    3. Sadayuki Yagi & Abolfazl Mohammadian, 2007. "Policy Simulation for New BRT and Area Pricing Alternatives Using an Opinion Survey in Jakarta," Transportation Planning and Technology, Taylor & Francis Journals, vol. 31(5), pages 589-612, September.
    4. Silvia Banfi & Mehdi Farsi & Massimo Filippini, 2009. "An Empirical Analysis Of Child Care Demand In Switzerland," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 80(1), pages 37-66, March.
    5. Banfi, Silvia & Farsi, Mehdi & Filippini, Massimo & Jakob, Martin, 2008. "Willingness to pay for energy-saving measures in residential buildings," Energy Economics, Elsevier, vol. 30(2), pages 503-516, March.
    6. Chen, Kee-Kuo & Ho, Hui-Ping & Chang, Ching-Ter, 2015. "Estimating attributes importance for container shipping industry by closing the listening gap with maximum convergent validity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 145-163.
    7. Razzolini, Tiziano, 2013. "How much trustworthy and salubrious an organic jam should be? The impact of organic logo on the Italian jam market," Food Policy, Elsevier, vol. 43(C), pages 1-13.
    8. Claudy, Marius C. & Michelsen, Claus & O'Driscoll, Aidan, 2011. "The diffusion of microgeneration technologies - assessing the influence of perceived product characteristics on home owners' willingness to pay," Energy Policy, Elsevier, vol. 39(3), pages 1459-1469, March.

  114. Franses, Ph.H.B.F., 2002. "On the diffusion of scientific publications; the case of Econometrica 1987," Econometric Institute Research Papers EI 2002-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2009. "Cointegration in a historical perspective," Econometric Institute Research Papers EI 2009-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Fok, D. & Franses, Ph.H.B.F., 2005. "Modeling the diffusion of scientific publications," Econometric Institute Research Papers EI 2005-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Richard S. J. Tol, 2011. "Credit where credit’s due: accounting for co-authorship in citation counts," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 291-299, October.
    4. Fragiskos Archontakis & Rocco Mosconi, 2021. "Søren Johansen and Katarina Juselius: A Bibliometric Analysis of Citations through Multivariate Bass Models," Econometrics, MDPI, vol. 9(3), pages 1-28, August.
    5. Erjen Van Nierop, 2009. "Why do statistics journals have low impact factors?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 52-62, February.
    6. García-Suaza, Andrés & Otero, Jesus & Winkelmann, Rainer, 2018. "Early Career Research Production in Economics: Does Mentoring Matter?," IZA Discussion Papers 11976, Institute of Labor Economics (IZA).
    7. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Rousseau, Ronald & Hu, Xiaojun, 2013. "Two time series, their meaning and some applications," Journal of Informetrics, Elsevier, vol. 7(3), pages 603-610.
    9. Liu, Yuxian & Rousseau, Ronald, 2008. "Definitions of time series in citation analysis with special attention to the h-index," Journal of Informetrics, Elsevier, vol. 2(3), pages 202-210.

  115. Jeanine Kippers & Erjen van Nierop & Richard Paap & Philip Hans Franses, 2002. "An Empirical Study of Cash Payments," Tinbergen Institute Discussion Papers 02-075/4, Tinbergen Institute.

    Cited by:

    1. Bijwaard, G.E. & Franses, Ph.H.B.F., 2006. "Does rounding matter for payment efficiency?," Econometric Institute Research Papers EI 2006-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Kippers, J. & Franses, Ph.H.B.F., 2003. "An empirical analysis of euro cash payments," Econometric Institute Research Papers EI 2003-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Joshi Harit & Mukherjee, Saral, 2017. "Transitions in currency denomination structure as supply disruption and demand distortion: Efficiency, Effectiveness and Bullwhip," IIMA Working Papers WP 2017-05-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    4. Kippers, J. & Franses, Ph.H.B.F., 2003. "Do we need all Euro denominations?," Econometric Institute Research Papers EI 2003-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Bijwaard, Govert E. & Franses, Philip Hans, 2009. "The effect of rounding on payment efficiency," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1449-1461, February.
    6. Franses, Ph.H.B.F. & Kippers, J., 2003. "How do we pay with euro notes? Empirical evidence from Monopoly experiments," Econometric Institute Research Papers EI 2003-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Philip Hans Franses & Max Welz, 2019. "Cash Use of the Taiwan Dollar: Is It Efficient? †," JRFM, MDPI, vol. 12(1), pages 1-6, January.

  116. Rutger van Oest & Richard Paap & Philip Hans Franses, 2002. "A Joint Framework for Category Purchase and Consumption Behavior," Tinbergen Institute Discussion Papers 02-124/4, Tinbergen Institute.

    Cited by:

    1. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  117. Franses, Ph.H.B.F. & Cramer, J.S., 2002. "On the number of categories in an ordered regression model," Econometric Institute Research Papers EI 2002-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Staus, Alexander, 2007. "An Ordinal Regression Model using Dealer Satisfaction Data," Working Papers 98632, Universitaet Hohenheim, Institute of Agricultural Policy and Agricultural Markets.
    2. Jan Schiefer & Monika Hartmann, 2008. "Determinants of competitive advantage for German food processors," Agribusiness, John Wiley & Sons, Ltd., vol. 24(3), pages 306-319.
    3. Lake, James & Millimet, Daniel L., 2014. "An Empirical Analysis of Trade-Related Redistribution and the Political Viability of Free Trade," IZA Discussion Papers 8086, Institute of Labor Economics (IZA).
    4. Ebru a layan-Akay & Muhammed H. Van, 2017. "Determinants of the Levels of Development Based on the Human Development Index:Bayesian Ordered Probit Model," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 425-431.
    5. Li-Wei Chao & José A. Pagán & Beth J. Soldo, 2008. "End-of-Life Medical Treatment Choices: Do Survival Chances and Out-of-Pocket Costs Matter?," Medical Decision Making, , vol. 28(4), pages 511-523, July.

  118. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    2. Epstein, Leonardo D. & Inostroza-Quezada, Ignacio E. & Goodstein, Ronald C. & Choi, S. Chan, 2021. "Dynamic effects of store promotions on purchase conversion: Expanding technology applications with innovative analytics," Journal of Business Research, Elsevier, vol. 128(C), pages 279-289.
    3. Ching, Andrew & Erdem, Tulin & Keane, Michael, 2007. "The Price Consideration Model of Brand Choice," MPRA Paper 4686, University Library of Munich, Germany.

  119. van Nierop, J.E.M. & Fok, D. & Franses, Ph.H.B.F., 2002. "Sales Models For Many Items Using Attribute Data," ERIM Report Series Research in Management ERS-2002-65-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Paul H. Jensen & Elizabeth Webster, 2008. "Labelling Characteristics And Demand For Retail Grocery Products In Australia," Australian Economic Papers, Wiley Blackwell, vol. 47(2), pages 129-140, June.

  120. Hyung, N. & Franses, Ph.H.B.F., 2002. "Inflation rates; long-memoray, level shifts, or both?," Econometric Institute Research Papers EI 2002-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," JRFM, MDPI, vol. 7(2), pages 1-30, June.
    2. Scharth, Marcel & Medeiros, Marcelo C., 2009. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
    3. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    4. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," Working Papers in Economics 10/26, University of Canterbury, Department of Economics and Finance.

  121. Franses, Ph.H.B.F., 2002. "On modeling panels of time series," Econometric Institute Research Papers EI 2002-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Martin Burda & Roman Liesenfeld & Jean-Francois Richard, 2008. "Bayesian Analysis of a Probit Panel Data Model with Unobserved Individual Heterogeneity and Autocorrelated Errors," Working Papers tecipa-321, University of Toronto, Department of Economics.

  122. Sloot, L.M. & Verhoef, P.C. & Franses, Ph.H.B.F., 2002. "The impact of brand and category characteristics on consumer stock-out reactions," ERIM Report Series Research in Management ERS-2002-106-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Lee, Richard & Murphy, Jamie, 2008. "The Moderating Influence of Enjoyment on Customer Loyalty," Australasian marketing journal, Elsevier, vol. 16(2), pages 11-21.

  123. Franses, Ph.H.B.F., 2002. "From first submission to citation: an empirical analysis," Econometric Institute Research Papers EI 2002-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Gao, Ying, 2009. "Single versus multiple submissions in the publication process," ISU General Staff Papers 200901010800001539, Iowa State University, Department of Economics.

  124. Vogelsang, Timothy J. & Franses, Philip Hans, 2001. "Testing for Common Deterministic Trend Slopes," Working Papers 01-15, Cornell University, Center for Analytic Economics.

    Cited by:

    1. Sobreira, Nuno & Nunes, Luis C., 2012. "Tests for Multiple Breaks in the Trend with Stationary or Integrated Shocks," Insper Working Papers wpe_290, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    2. R. Velazquez & Noriega & A., 2004. "International evidence on monetary neutrality under broken trend stationary models," Computing in Economics and Finance 2004 282, Society for Computational Economics.
    3. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    4. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.
    5. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.
    6. Yonghui Zhang & Liangjun Su & Peter C.B. Phillips, 2011. "Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects," Cowles Foundation Discussion Papers 1832, Cowles Foundation for Research in Economics, Yale University.
    7. Joseph P. Byrne & Roger Perman, 2006. "Unit Roots and Structural Breaks: A Survey of the Literature," Working Papers 2006_10, Business School - Economics, University of Glasgow.
    8. Vogelsang, Timothy & Nawaz, Nasreen, 2015. "Estimation and Inference of Linear Trend Slope Ratios with an Application to Global Temperature Data," MPRA Paper 117435, University Library of Munich, Germany.
    9. Pierre Perron & Tomoyoshi Yabu, "undated". "Estimating Deterministic Trends with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2006-012, Boston University - Department of Economics, revised Feb 2006.
    10. Xu, Ke-Li, 2012. "Robustifying multivariate trend tests to nonstationary volatility," Journal of Econometrics, Elsevier, vol. 169(2), pages 147-154.
    11. Noriega, Antonio E. & Soria, Luis M. & Velázquez, Ramón, 2008. "International evidence on stochastic and deterministic monetary neutrality," Economic Modelling, Elsevier, vol. 25(6), pages 1261-1275, November.
    12. Sun, Yixiao, 2011. "Robust trend inference with series variance estimator and testing-optimal smoothing parameter," Journal of Econometrics, Elsevier, vol. 164(2), pages 345-366, October.
    13. Lyubchich, Vyacheslav & Gel, Yulia R., 2016. "A local factor nonparametric test for trend synchronism in multiple time series," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 91-104.
    14. Eun, Cheol S. & Lee, Jinsoo, 2010. "Mean-variance convergence around the world," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 856-870, April.
    15. Ross McKitrick & Timothy Vogelsang, 2011. "Multivariate trend comparisons between autocorrelated climate series with general trend regressors," Working Papers 1109, University of Guelph, Department of Economics and Finance.

  125. Charles S. Bos & Philip Hans Franses & Marius Ooms, 2001. "Inflation, Forecast Intervals and Long Memory Regression Models," Tinbergen Institute Discussion Papers 01-029/4, Tinbergen Institute.

    Cited by:

    1. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    2. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
    3. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    4. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    5. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    6. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    7. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    8. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2003. "Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach," Faculty Working Papers 01/03, School of Economics and Business Administration, University of Navarra.
    9. Philip Hans Franses, 2019. "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(2), pages 73-80, March.
    10. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    11. Luis A Gil-Alana & Christophe André & Rangan Gupta & Tsangyao Chang & Omid Ranjbar, 2015. "The Feldstein-Horioka Puzzle in South Africa: A Fractional Cointegration Approach," Working Papers 201501, University of Pretoria, Department of Economics.
    12. Luis Gil-Alana, 2008. "Real GDP growth rates across countries: long memory and mean shifts," Applied Economics Letters, Taylor & Francis Journals, vol. 15(6), pages 449-455.
    13. Hyung, N. & Franses, Ph.H.B.F., 2001. "Structural breaks and long memory in US inflation rates: do they matter for forecasting?," Econometric Institute Research Papers EI 2001-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Chien-Chiang Lee & Chun-Ping Chang, 2007. "Mean reversion of inflation rates in 19 OECD countries: Evidence from panel Lm unit root tests with structural breaks," Economics Bulletin, AccessEcon, vol. 3(23), pages 1-15.
    15. Luis A. Gil‐Alana, 2008. "Fractional integration and structural breaks at unknown periods of time," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 163-185, January.
    16. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    17. Manmohan S. Kumar & Tatsuyoshi Okimoto, 2007. "Dynamics of Persistence in International Inflation Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1457-1479, September.
    18. Heinen, Florian & Sibbertsen, Philipp & Kruse, Robinson, 2009. "Forecasting long memory time series under a break in persistence," Hannover Economic Papers (HEP) dp-433, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    19. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    20. Claudio Morana & Fabio Cesare Bagliano, 2007. "Inflation and monetary dynamics in the USA: a quantity-theory approach," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 229-244.
    21. J. Cunado & L.A. Gil-Alana & F. P Erez de Gracia, 2008. "Fractional Integration and Structural Breaks: Evidence from International Monthly Arrivals in the USA," Tourism Economics, , vol. 14(1), pages 13-23, March.
    22. Chu Shiou-Yen & Shane Christopher, 2017. "Using the hybrid Phillips curve with memory to forecast US inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-16, September.
    23. Juncal Cunado & Luis Alberiko Gil-Alana & Fernando Perez de Gracia, 2008. "New Evidence on US Current Account Sustainability," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 1-21, April.
    24. Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
    25. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    26. Luis A. Gil-Alana & Antonio Moreno & Seonghoon Cho, 2009. "The Deaton paradox in a long memory context with structural breaks," Faculty Working Papers 03/09, School of Economics and Business Administration, University of Navarra.
    27. Gil-Alana, Luis A. & Mudida, Robert, 2017. "CPI and inflation in Kenya. Structural breaks, non-linearities and dependence," International Economics, Elsevier, vol. 150(C), pages 72-79.
    28. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 594-616.
    29. Laura Mayoral, 2015. "The Persistence of Inflation in OECD Countries:a Fractionally Integrated Approach," Working Papers 259, Barcelona School of Economics.
    30. Lovcha, Yuliya & Pérez Laborda, Àlex, 2013. "A fractionally integrated approach to monetary policy and inflation dynamics," Working Papers 2072/211795, Universitat Rovira i Virgili, Department of Economics.
    31. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    32. Dmytro Krukovets & Olesia Verchenko, 2019. "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20.
    33. Cunado, J. & Gil-Alana, L. A. & Perez de Gracia, F., 2004. "Is the US fiscal deficit sustainable?: A fractionally integrated approach," Journal of Economics and Business, Elsevier, vol. 56(6), pages 501-526.
    34. Georgios KOURETAS & Mark E. WOHAR, 2010. "The Dynamics of Inflation: A Study of a Large Number of Countries," EcoMod2010 259600096, EcoMod.
    35. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    36. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
    37. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    38. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    39. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    40. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    41. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2021. "Long-memory modeling and forecasting: evidence from the U.S. historical series of inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 289-310, December.
    42. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    43. Luis A. Gil-Alana & Yadollah Dadgar & Rouhollah Nazari, 2019. "Iranian inflation: peristence and structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 398-408, April.

  126. Donkers, A.C.D. & Franses, Ph.H.B.F. & Verhoef, P.C., 2001. "Using Selective Sampling for Binary Choice Models to Reduce Survey Costs," ERIM Report Series Research in Management ERS-2001-67-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics (QME), Springer, vol. 5(2), pages 163-190, June.

  127. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    2. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    3. Malgorzata Olszak & Mateusz Pipien & Iwona Kowalska & Sylwia Roszkowska, 2015. "Do regulations and supervision shape the capital crunch effect of large banks in the EU?," Faculty of Management Working Paper Series 32015, University of Warsaw, Faculty of Management.
    4. Xiao, Yi & Liu, John J. & Hu, Yi & Wang, Yingfeng & Lai, Kin Keung & Wang, Shouyang, 2014. "A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 1-11.
    5. Ubilava, David, 2014. "On the Relationship between Financial Instability and Economic Performance: Stressing the Business of Nonlinear Modelling," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170222, Agricultural and Applied Economics Association.
    6. Elena Ganón & Ina Tiscordio, 2007. "Un análisis de variables fiscales del Gobierno Central del Uruguay para el período 1989-2006," Documentos de trabajo 2007005, Banco Central del Uruguay.
    7. Giancarlo Bruno, 2009. "Non-linear relation between industrial production and business surveys data," ISAE Working Papers 119, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    8. Marc Lavoie & Gabriel Rodríguez, 2005. "The Economic Impact of Professional Teams on Monthly Hotel Occupancy Rates of Canadian Cities," Journal of Sports Economics, , vol. 6(3), pages 314-324, August.
    9. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    10. Yi Xiao & Shouyang Wang & Ming Xiao & Jin Xiao & Yi Hu, 2017. "The Analysis for the Cargo Volume with Hybrid Discrete Wavelet Modeling," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 851-863, May.
    11. Petropoulos, Fotios & Makridakis, Spyros & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2014. "‘Horses for Courses’ in demand forecasting," European Journal of Operational Research, Elsevier, vol. 237(1), pages 152-163.
    12. Charles S. Bos & Siem Jan Koopman, 2010. "Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production," Tinbergen Institute Discussion Papers 10-017/4, Tinbergen Institute.
    13. Małgorzata Olszak & Mateusz Pipień & Sylwia Roszkowska & Iwona Kowalska, 2018. "The Impact of Capital on Lending in Economic Downturns and Investor Protection – the Case of Large EU Banks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(2), pages 133-167, June.
    14. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
    15. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    16. Giulio Galdi & Roberto Casarin & Davide Ferrari & Carlo Fezzi & Francesco Ravazzolo, 2022. "Nowcasting industrial production using linear and non-linear models of electricity demand," DEM Working Papers 2022/2, Department of Economics and Management.
    17. Francisco Salas-Molina & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Montserrat Guillen & Francisco J. Martin, 2016. "Empirical analysis of daily cash flow time series and its implications for forecasting," Papers 1611.04941, arXiv.org, revised Jun 2017.
    18. Tine Van Calster & Filip Van den Bossche & Bart Baesens & Wilfried Lemahieu, 2020. "Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective," Papers 2002.00949, arXiv.org.
    19. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    20. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1109, Universitá degli Studi di Milano.
    21. Beckmann, Joscha, 2013. "Nonlinear adjustment, purchasing power parity and the role of nominal exchange rates and prices," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 176-190.
    22. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    23. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    24. Mubariz Hasanov & Aysen Arac & Funda Telatar, 2012. "Nonlinearity and Structural Stability in the Phillips Curve: Evidence from Turkey," Hacettepe University Department of Economics Working Papers 20123, Hacettepe University, Department of Economics.
    25. Donya Rahmani & Saeed Heravi & Hossein Hassani & Mansi Ghodsi, 2016. "Forecasting time series with structural breaks with Singular Spectrum Analysis, using a general form of recurrent formula," Papers 1605.02188, arXiv.org.
    26. Xiao Yi & Liu John J. & Hu Yi & Wang Yingfeng, 2014. "Time Series Forecasting Using a Hybrid Adaptive Particle Swarm Optimization and Neural Network Model," Journal of Systems Science and Information, De Gruyter, vol. 2(4), pages 335-344, August.
    27. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.

  128. Koopman, S.J. & Franses, Ph.H.B.F., 2001. "Constructing seasonally adjusted data with time-varying confidence intervals," Econometric Institute Research Papers EI 2001-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    2. Jamel Gatfaoui & Eric Girardin, 2015. "Comovement of Chinese provincial business cycles," Post-Print hal-01456105, HAL.
    3. Gebhard Flaig, 2003. "Time Series Properties of the German Monthly Production Index," CESifo Working Paper Series 833, CESifo.

  129. Dekker, D.J. & Franses, Ph.H.B.F. & Krackhardt, D., 2001. "An Equilibrium-Correction Model for Dynamic Network Data," ERIM Report Series Research in Management ERS-2001-39-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Buechel, Berno & Buskens, Vincent, 2011. "The dynamics of closeness and betweenness," Center for Mathematical Economics Working Papers 398, Center for Mathematical Economics, Bielefeld University.
    2. Dekker, D.J. & Krackhardt, D. & Franses, Ph.H.B.F., 2002. "Dynamic Effects of Trust and Cognitive Social Structures on Information Transfer Relationships," ERIM Report Series Research in Management ERS-2002-33-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Aalbers, Rick & Dolfsma, Wilfred & Koppius, Otto, 2013. "Individual connectedness in innovation networks: On the role of individual motivation," Research Policy, Elsevier, vol. 42(3), pages 624-634.

  130. Vroomen, B.L.K. & Franses, Ph.H.B.F. & van Nierop, J.E.M., 2001. "Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks," ERIM Report Series Research in Management ERS-2001-10-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Y Hayashi & M-H Hsieh & R Setiono, 2009. "Predicting consumer preference for fast-food franchises: a data mining approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1221-1229, September.
    2. Potharst, R. & van Rijthoven, M. & van Wezel, M.C., 2005. "Modeling brand choice using boosted and stacked neural networks," Econometric Institute Research Papers EI 2005-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Manash Pratim Kashyap, 2011. "Brand Categorization Process for Staple Goods: Comparison between Rural and Urban Customers," Information Management and Business Review, AMH International, vol. 2(4), pages 162-172.
    4. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.

  131. Franses, Ph.H.B.F. & van der Leij, M.J. & Paap, R., 2001. "Modeling and forecasting outliers and level shifts in absolute returns," Econometric Institute Research Papers EI 2001-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    2. Richard Paap & Philip Hans Franses & Marco Van Der Leij, 2002. "Modelling and forecasting level shifts in absolute returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 601-616.

  132. Donkers, A.C.D. & Jonker, J.-J. & Franses, Ph.H.B.F. & Paap, R., 2001. "Deriving Target Selection Rules from Endogenously Selected Samples," ERIM Report Series Research in Management ERS-2001-68-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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    1. Rust, Roland T. & Kumar, V. & Venkatesan, Rajkumar, 2011. "Will the frog change into a prince? Predicting future customer profitability," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 281-294.
    2. Donkers, Bas & van Diepen, Merel & Franses, Philip Hans, 2017. "Do charities get more when they ask more often? Evidence from a unique field experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 66(C), pages 58-65.
    3. Schröder, Nadine & Hruschka, Harald, 2016. "Investigating the effects of mailing variables and endogeneity on mailing decisions," European Journal of Operational Research, Elsevier, vol. 250(2), pages 579-589.
    4. Marc Fischer, 2019. "Practice Prize Paper–Managing Advertising Campaigns for New Product Launches: An Application at Mercedes-Benz," Marketing Science, INFORMS, vol. 38(2), pages 343-359, March.
    5. David A. Schweidel & George Knox, 2013. "Incorporating Direct Marketing Activity into Latent Attrition Models," Marketing Science, INFORMS, vol. 32(3), pages 471-487, May.
    6. Lemmens, A. & Croux, C., 2006. "Bagging and boosting classification trees to predict churn," Other publications TiSEM d5cb664d-5859-44db-a621-e, Tilburg University, School of Economics and Management.
    7. Gázquez-Abad, Juan Carlos & Canniére, Marie Hélène De & Martínez-López, Francisco J., 2011. "Dynamics of Customer Response to Promotional and Relational Direct Mailings from an Apparel Retailer: The Moderating Role of Relationship Strength," Journal of Retailing, Elsevier, vol. 87(2), pages 166-181.
    8. Thomas, Suman Ann & Feng, Shanfei & Krishnan, Trichy V., 2015. "To retain? To upgrade? The effects of direct mail on regular donation behavior," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 48-63.
    9. van Diepen, Merel & Donkers, Bas & Franses, Philip Hans, 2009. "Does irritation induced by charitable direct mailings reduce donations?," International Journal of Research in Marketing, Elsevier, vol. 26(3), pages 180-188.
    10. Haupt, Johannes & Lessmann, Stefan, 2022. "Targeting customers under response-dependent costs," European Journal of Operational Research, Elsevier, vol. 297(1), pages 369-379.
    11. Haupt, Johannes & Lessmann, Stefan, 2020. "Targeting Cutsomers Under Response-Dependent Costs," IRTG 1792 Discussion Papers 2020-005, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Hruschka, Harald, 2010. "Considering endogeneity for optimal catalog allocation in direct marketing," European Journal of Operational Research, Elsevier, vol. 206(1), pages 239-247, October.
    13. Piersma, Nanda & Jonker, Jedid-Jah, 2004. "Determining the optimal direct mailing frequency," European Journal of Operational Research, Elsevier, vol. 158(1), pages 173-182, October.
    14. Jonker, J.-J. & Piersma, N. & Van den Poel, D., 2002. "Joint optimization of customer segmentation and marketing policy to maximize long-term profitability," Econometric Institute Research Papers EI 2002-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Sarkar, Mainak & De Bruyn, Arnaud, 2021. "LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning," Journal of Interactive Marketing, Elsevier, vol. 53(C), pages 80-95.
    16. Feld, Sebastian & Frenzen, Heiko & Krafft, Manfred & Peters, Kay & Verhoef, Peter C., 2013. "The effects of mailing design characteristics on direct mail campaign performance," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 143-159.
    17. Park, Chang Hee & Agarwal, Manoj K., 2018. "The order effect of advertisers on consumer search behavior in sponsored search markets," Journal of Business Research, Elsevier, vol. 84(C), pages 24-33.
    18. Johannes Haupt & Stefan Lessmann, 2020. "Targeting customers under response-dependent costs," Papers 2003.06271, arXiv.org, revised Aug 2021.

  133. Hyung, N. & Franses, Ph.H.B.F., 2001. "Structural breaks and long memory in US inflation rates: do they matter for forecasting?," Econometric Institute Research Papers EI 2001-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Ciner, Cetin, 2011. "Commodity prices and inflation: Testing in the frequency domain," Research in International Business and Finance, Elsevier, vol. 25(3), pages 229-237, September.
    2. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    3. Jonathan Dark, 2004. "Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures," Monash Econometrics and Business Statistics Working Papers 5/04, Monash University, Department of Econometrics and Business Statistics.
    4. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    5. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    6. Chien-Chiang Lee & Chun-Ping Chang, 2007. "Mean reversion of inflation rates in 19 OECD countries: Evidence from panel Lm unit root tests with structural breaks," Economics Bulletin, AccessEcon, vol. 3(23), pages 1-15.
    7. Caporale, Guglielmo Maria & Gil-Alaña, Luis, 2019. "Testing the Fisher hypothesis in the G-7 countries using I(d) techniques," International Economics, Elsevier, vol. 159(C), pages 140-150.
    8. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    9. WANG, Shin-Huei & BAUWENS, Luc & HSIAO, Cheng, 2012. "Forecasting long memory processes subject to structural breaks," LIDAM Discussion Papers CORE 2012048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    11. Mateo Isoardi & Luis A. Gil-Alana, 2019. "Inflation in Argentina: Analysis of Persistence Using Fractional Integration," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(2), pages 204-223, April.
    12. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
    13. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    14. Jerry Coakley & Jian Dollery & Neil Kellard, 2011. "Long memory and structural breaks in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(11), pages 1076-1113, November.
    15. Goliński, Adam & Zaffaroni, Paolo, 2016. "Long memory affine term structure models," Journal of Econometrics, Elsevier, vol. 191(1), pages 33-56.
    16. Jonathan Dark, 2004. "Bivariate error correction FIGARCH and FIAPARCH models on the Australian All Ordinaries Index and its SPI futures," Monash Econometrics and Business Statistics Working Papers 4/04, Monash University, Department of Econometrics and Business Statistics.
    17. Hwang, Eunju & Shin, Dong Wan, 2013. "A CUSUM test for a long memory heterogeneous autoregressive model," Economics Letters, Elsevier, vol. 121(3), pages 379-383.
    18. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    19. Morana Claudio, 2002. "Common Persistent Factors in Inflation and Excess Nominal Money Growth and a New Measure of Core Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-40, November.
    20. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    21. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    22. Hwang, Eunju & Shin, Dong Wan, 2015. "A CUSUMSQ test for structural breaks in error variance for a long memory heterogeneous autoregressive model," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 167-176.
    23. Narayan, Seema & Narayan, Paresh Kumar, 2013. "The inflation–output nexus: Empirical evidence from India, South Africa, and Brazil," Research in International Business and Finance, Elsevier, vol. 28(C), pages 19-34.

  134. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2001. "Econometric Analysis of the Market Share Attraction Model," ERIM Report Series Research in Management ERS-2001-25-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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    1. Noordegraaf-Eelens, L.H.J. & Franses, Ph.H.B.F., 2014. "Do loss profiles on the mortgage market resonate with changes in macro economic prospects, business cycle movements or policy measures?," Econometric Institute Research Papers EI 2014-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Datta, Hannes & Ailawadi, Kusum L. & van Heerde, H.J., 2016. "How well does consumer-based brand equity align with sales-based brand equity and marketing mix response?," Other publications TiSEM 341e600f-af04-42e7-9668-a, Tilburg University, School of Economics and Management.

  135. Boswijk, H.P. & Franses, Ph.H.B.F., 2001. "Robust inference on average economic growth," Econometric Institute Research Papers EI 2001-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    1. G. K. Randolph Tan, 2006. "Robust Inference for Measures of Persistence in Singapore Sectoral Property Price Indexes," Journal of Property Research, Taylor & Francis Journals, vol. 23(4), pages 305-321, October.
    2. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.

  136. Verhoef, P.C. & Franses, Ph.H.B.F. & Donkers, A.C.D., 2001. "Changing Perceptions and Changing Behavior in Customer Relationships," ERIM Report Series Research in Management ERS-2001-31-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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    1. Verhoef, P.C. & Antonides, G. & de Hoog, A.N., 2002. "Service Processes as a Sequence of Events," ERIM Report Series Research in Management ERS-2002-105-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  137. Pelzer, B. & Eisinga, R. & Franses, Ph.H.B.F., 2001. "Inferring transition probabilities from repeated cross sections: a cross-level inference approach to US presidential voting," Econometric Institute Research Papers EI 2001-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    1. Ben Pelzer & Rob Eisinga, 2002. "Bayesian estimation of transition probabilities from repeated cross sections," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(1), pages 23-33, February.

  138. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    1. Menzie Chinn & Laurent Ferrara & Valérie Mignon, 2013. "Post-recession US employment through the lens of a non-linear Okun’s law," EconomiX Working Papers 2013-12, University of Paris Nanterre, EconomiX.
    2. JamesR. Lothian & MarkP. Taylor, 2008. "Real Exchange Rates Over the Past Two Centuries: How Important is the Harrod-Balassa-Samuelson Effect?," Economic Journal, Royal Economic Society, vol. 118(532), pages 1742-1763, October.
    3. Agnello, Luca & Castro, Vítor & Sousa, Ricardo M., 2012. "How does fiscal policy react to wealth composition and asset prices?," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 874-890.
    4. Yang Fuyu & Leon-Gonzalez Roberto, 2010. "Bayesian Estimation and Model Selection in the Generalized Stochastic Unit Root Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-38, September.
    5. Peter Martey Addo & Monica Billio & Dominique Guegan, 2011. "A New Modelling Test: The Univariate MT-STAR Model," Documents de travail du Centre d'Economie de la Sorbonne 11083r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Aug 2013.
    6. Fredj Jawadi & Souhir Chlibi & Abdoulkarim Idi Cheffou, 2019. "Computing stock price comovements with a three-regime panel smooth transition error correction model," Annals of Operations Research, Springer, vol. 274(1), pages 331-345, March.
    7. Libman, Emiliano, 2017. "Asymmetric Monetary and Exchange Rate Policies in Latin America," MPRA Paper 78864, University Library of Munich, Germany.
    8. Param Silvapulle & Titi Kanti Lestari & Jae Kim, 2004. "Nonlinear Modelling of Purchasing Power Parity in Indonesia," Econometric Society 2004 Australasian Meetings 316, Econometric Society.
    9. Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2013. "State-Dependent Threshold Smooth Transition Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 835-854, December.
    10. Rodriguez, Gabriel & Sloboda, Michael J., 2005. "Modeling nonlinearities and asymmetries in quarterly revenues of the US telecommunications industry," Structural Change and Economic Dynamics, Elsevier, vol. 16(1), pages 137-158, March.
    11. Cengiz, Sibel & Sahin, Afsin, 2013. "Modelling Nonlinear Behavior of Labor Force Participation Rate by STAR: An Application for Turkey," MPRA Paper 47805, University Library of Munich, Germany, revised 07 May 2013.
    12. Frédérique Bec & Mélika Ben Salem & Marine Carrasco, 2009. "Detecting Mean Reversion in Real Exchange Rates from a Multiple Regime STAR Model," CIRANO Working Papers 2009s-18, CIRANO.
    13. Thouraya Boujelbène Dammak & Kamel Helali, 2016. "A Nonlinear Approach to Tunisian Inflation Rate," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(61), pages 147-164, September.
    14. Barbara Annicchiarico & Anna Rita Bennato & Emilio Zanetti Chini, 2014. "150 Years of Italian CO2 Emissions and Economic Growth," CEIS Research Paper 320, Tor Vergata University, CEIS, revised 31 Jul 2014.
    15. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, University Library of Munich, Germany, revised 05 Aug 2005.
    16. Hamulczuk, Mariusz, 2020. "Spatial Integration of Agricultural Commodity Markets – Methodological Problems," Problems of Agricultural Economics / Zagadnienia Ekonomiki Rolnej 311225, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).
    17. Rickard Sandberg, 2016. "Testing for unit roots in nonlinear heterogeneous panels with smoothly changing trends: an application to Scandinavian unemployment rates," Empirical Economics, Springer, vol. 51(3), pages 1053-1083, November.
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    20. Andres Gonzalez & Timo Terasvirta & Dick van Dijk, 2005. "Panel Smooth Transition Regression Models," Research Paper Series 165, Quantitative Finance Research Centre, University of Technology, Sydney.
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    22. Harvey, A. & Simons, J., 2024. "Hidden Threshold Models with applications to asymmetric cycles," Cambridge Working Papers in Economics 2448, Faculty of Economics, University of Cambridge.
    23. Paul Alagidede & Theodore Panagiotidis, 2009. "Modelling stock returns in Africa’s emerging equity markets," Discussion Paper Series 2009_01, Department of Economics, University of Macedonia, revised Jan 2009.
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    35. Rahbar , Farhad & Behzadi Soufiani , Mohsen, 2021. "The Impact of Macroeconomic and Banking Variables on Non-Performing Loans in Oil Cycles: Evidence from Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 135-164, June.
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    39. Ana Beatriz Galvão & Michael T. Owyang, 2018. "Financial Stress Regimes and the Macroeconomy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(7), pages 1479-1505, October.
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    43. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
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    46. Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Studies in Nonlinear Dynamics and Wavelets for Business Cycle Analysis," Documents de travail du Centre d'Economie de la Sorbonne 12023r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Nov 2013.
    47. Samuel S Jibao & Niek Schoeman & Ruthira Naraidoo, 2010. "Fiscal Regime Changes and the Sustainability of Fiscal Imbalance in South Africa: A Smooth Transition Error-Correction Approach," Working Papers 201023, University of Pretoria, Department of Economics.
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    50. Hyeongwoo Kim & Young-Kyu Moh, 2012. "The Yen Real Exchange Rate May Not Be Stationary After All: New Evidence from Non-linear Unit-Root Tests," Auburn Economics Working Paper Series auwp2012-02, Department of Economics, Auburn University.
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    Cited by:

    1. Baghli Mustapha, 2005. "Nonlinear Error-Correction Models for the FF/DM Rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-43, March.
    2. Galvão, Ana Beatriz C., 2003. "Multivariate Threshold Models: TVARs and TVECMs," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(1), May.
    3. Ólan T. Henry & Nilss Olekalns & Kalvinder K. Shields, 2013. "Quantifying time variation and asymmetry in measures of covariance risk: a simulation approach," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 18, pages 457-476, Edward Elgar Publishing.
    4. Ivan Paya & David A. Peel, 2006. "Temporal aggregation of an ESTAR process: some implications for purchasing power parity adjustment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 655-668, July.
    5. Hassan Belkacem Ghassan & Mohammed Souissi & Mohammed Kbiri Alaoui, 2009. "An Alternative Identification of the Economic Shocks in SVAR Models," Economics Bulletin, AccessEcon, vol. 29(2), pages 1019-1026.
    6. Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), 2013. "Handbook of Research Methods and Applications in Empirical Finance," Books, Edward Elgar Publishing, number 14545, March.
    7. I Paya & D Peel, 2005. "A new analysis of the determinants of the real dollar-sterling exchange rate: 1871-1994," Working Papers 565953, Lancaster University Management School, Economics Department.
    8. Ubilava, David, 2014. "The ENSO Effect on World Wheat Market Dynamics: Smooth Transitions in Asymmetric Price Transmission," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170223, Agricultural and Applied Economics Association.
    9. Gabreyohannes, Emmanuel, 2010. "A nonlinear approach to modelling the residential electricity consumption in Ethiopia," Energy Economics, Elsevier, vol. 32(3), pages 515-523, May.
    10. Olan T. Henry & Nilss Olekalns & Kalvinder Shields, 2004. "Time Variation And Asymmetry In The World Price Of Covariance Risk: The Implications For International Diversification," Department of Economics - Working Papers Series 907, The University of Melbourne.
    11. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    12. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.

  140. van Nierop, J.E.M. & Paap, R. & Bronnenberg, B. & Franses, Ph.H.B.F., 2000. "Modeling Unobserved Consideration Sets for Household Panel Data," ERIM Report Series Research in Management ERS-2000-42-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Paap, R. & van Nierop, J.E.M. & van Heerde, H.J. & Wedel, M. & Franses, Ph.H.B.F. & Alsem, K.J., 2000. "Consideration sets, intentions and the inclusion of "Don't know" in a two-stage model for voter choice," Econometric Institute Research Papers EI 2000-33/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  141. Franses, Ph.H.B.F. & de Bruin, P. & van Dijk, D.J.C., 2000. "Seasonal smooth transition autoregression," Econometric Institute Research Papers EI 2000-06/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Raimundo Soto, 2002. "Ajuste Estacional e Integración en Variables Macroeconómicas," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 39(116), pages 135-155.
    2. Kumawat, Lokendra, 2010. "Effect of Rainfall on Seasonals in Indian Manufacturing Production: Evidence from Sectoral Data," MPRA Paper 25300, University Library of Munich, Germany.
    3. Nasr, Adnen Ben & Balcilar, Mehmet & Ajmi, Ahdi N. & Aye, Goodness C. & Gupta, Rangan & van Eyden, Reneé, 2015. "Causality between inflation and inflation uncertainty in South Africa: Evidence from a Markov-switching vector autoregressive model," Emerging Markets Review, Elsevier, vol. 24(C), pages 46-68.
    4. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    5. Pami Dua & Lokendra Kumawat, 2007. "Modelling Seasonal Dynamics in Indian Industrial Production--An Extention of TV-STAR Model," Working papers 162, Centre for Development Economics, Delhi School of Economics.
    6. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    7. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2008. "Modelo de Crescimento Baseado nas Exportações: Evidências empíricas para Chile, Brasil e México, em uma perspectiva Não Linear," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807170923500, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

  142. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Cubadda, Gianluca & Omtzigt, Pieter, 2003. "Small Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems," Economics & Statistics Discussion Papers esdp03012, University of Molise, Department of Economics.
    2. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    3. Allen, P. Geoffrey & Fildes, Robert, 2004. "Levels, Differences And Ecms - Principles For Improved Econometric Forecasting," Working Paper Series 14501, University of Massachusetts, Amherst, Department of Resource Economics.
    4. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.
    6. Anna Czapkiewicz & Marta Stachowicz, 2016. "The long-run relationship between the stock market and main macroeconomic variables in Poland," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 17(1), pages 7-20.
    7. Piotr Białowolski & Tomasz Kuszewski & Bartosz Witkowski, 2014. "Bayesian averaging of classical estimates in forecasting macroeconomic indicators with application of business survey data," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(1), pages 53-68, February.
    8. Justyna Wr'oblewska, 2020. "Bayesian analysis of seasonally cointegrated VAR model," Papers 2012.14820, arXiv.org, revised Apr 2021.
    9. Jacek Kotlowski, 2005. "Money and prices in the Polish economy. Seasonal cointegration approach," Working Papers 20, Department of Applied Econometrics, Warsaw School of Economics.

  143. Jonker, J.-J. & Paap, R. & Franses, Ph.H.B.F., 2000. "Modeling charity donations: target selection, response time and gift size," Econometric Institute Research Papers EI 2000-07/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Zeynep B. Ugur, 2018. "Donate More, Be Happier! Evidence from the Netherlands," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 13(1), pages 157-177, March.
    2. Ugur, Z.B., 2013. "From headscarves to donation : Three essays on the economics of gender, health and happiness," Other publications TiSEM 9cfb068c-c08e-47aa-8c44-f, Tilburg University, School of Economics and Management.

  144. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Paap, R., 2000. "A nonlinear long memory model for US unemployment," Econometric Institute Research Papers EI 2000-30/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2004. "Non-Linearities And Fractional Integration In The Us Unemployment Rate," Public Policy Discussion Papers 04-17, Economics and Finance Section, School of Social Sciences, Brunel University.

  145. Fok, D. & Franses, Ph.H.B.F., 2000. "Forecasting Market Shares from Models for Sales," ERIM Report Series Research in Management ERS-2000-03-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Sanders, Nada R. & Manrodt, Karl B., 2003. "The efficacy of using judgmental versus quantitative forecasting methods in practice," Omega, Elsevier, vol. 31(6), pages 511-522, December.
    2. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Kanellos, Nikolaos & Katsianis, Dimitrios & Varoutas, Dimitrios, 2022. "Forecasting a telecommunications provider's market share," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265639, International Telecommunications Society (ITS).
    4. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2003. "Modeling Dynamic Effects of the Marketing Mix on Market Shares," ERIM Report Series Research in Management ERS-2003-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Alina Popa & Shahrazad Hadad & Robert Paiusan & Marian Nastase, 2018. "A New Method for Agricultural Market Share Assessment," Sustainability, MDPI, vol. 11(1), pages 1-13, December.
    6. Zuidwijk, R.A. & Kroon, L.G., 2000. "Integer Constraints for Train Series Connections," ERIM Report Series Research in Management ERS-2000-05-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.

  146. Paap, R. & van Nierop, J.E.M. & van Heerde, H.J. & Wedel, M. & Franses, Ph.H.B.F. & Alsem, K.J., 2000. "Consideration sets, intentions and the inclusion of "Don't know" in a two-stage model for voter choice," Econometric Institute Research Papers EI 2000-33/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Richard Paap, 2002. "What are the advantages of MCMC based inference in latent variable models?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(1), pages 2-22, February.
    2. Allenby, Greg M., 2017. "Structural forecasts for marketing data," International Journal of Forecasting, Elsevier, vol. 33(2), pages 433-441.

  147. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Madalina-Gabriela ANGHEL & Aurelian DIACONU, 2016. "Equilibrium and auto regression models used for macroeconomic prognosis," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(7), pages 70-78, July.
    2. virginie terraza & stephane mussard, 2007. "New trading risk indexes: application of the shapley value in finance," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.

  148. Franses, Ph.H.B.F. & Kunst, R.M., 1999. "Testing common deterministic seasonality," Econometric Institute Research Papers EI 9905-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Philip Hans Franses, 2006. "On modeling panels of time series," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(4), pages 438-456, November.

  149. Franses, Ph.H.B.F. & Slagter, E. & Cramer, J.S., 1999. "Censored regression analysis in large samples with many zero observations," Econometric Institute Research Papers EI 9939-A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Sabine Knapp & Philip Hans Franses, 2009. "Comprehensive Review of the Maritime Safety Regimes: Present Status and Recommendations for Improvements," Transport Reviews, Taylor & Francis Journals, vol. 30(2), pages 241-270, April.
    2. Fan, Di & Lo, Chris K.Y. & Zhou, Yi, 2021. "Sustainability risk in supply bases: The role of complexity and coupling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    3. Fok, Dennis & Franses, Philip Hans, 2002. "Ordered logit analysis for selectively sampled data," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 477-497, September.
    4. Barry L. Bayus, 2013. "Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community," Management Science, INFORMS, vol. 59(1), pages 226-244, June.
    5. Bashirzadeh, Yashar & Mai, Robert & Faure, Corinne, 2022. "How rich is too rich? Visual design elements in digital marketing communications," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 58-76.
    6. J.S. Cramer, 2000. "Scoring Bank Loans that may go wrong: A Case Study," Tinbergen Institute Discussion Papers 00-090/4, Tinbergen Institute.
    7. Fan, Di & Yeung, Andy C.L. & Yiu, Daphne W. & Lo, Chris K.Y., 2022. "Safety regulation enforcement and production safety: The role of penalties and voluntary safety management systems," International Journal of Production Economics, Elsevier, vol. 248(C).

  150. Rothman, P. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 1999. "A multivariate STAR analysis of the relationship between money and output," Econometric Institute Research Papers EI 9945-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Milas Costas & Legrenzi Gabriella, 2006. "Non-linear Real Exchange Rate Effects in the UK Labour Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-34, March.
    2. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    3. Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2007. "Multivariate contemporaneous threshold autoregressive models," Working Papers 2007-019, Federal Reserve Bank of St. Louis.
    4. Robert Sollis, 2005. "Evidence on purchasing power parity from univariate models: the case of smooth transition trend-stationarity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 79-98.
    5. Dimitris K. Christopoulos & Miguel A. León-Ledesma, 2008. "Testing for Granger (non-)causality in a time-varying coefficient VAR model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 293-303.
    6. Jonathan B. Hill, 2004. "Efficient Tests of Long-Run Causation in Trivariate VAR Processes with a Rolling Window Study of the Money-Income Relationship," Macroeconomics 0407013, University Library of Munich, Germany, revised 15 Feb 2006.
    7. Mendoza Lugo, Omar & Pedauga, Luis Enrique, 2006. "Efecto transferencia (pass-through) del tipo de cambio en los precios de bienes y servicios en Venezuela [Exchange rate pass-through on prices of goods and services in Venezuela]," MPRA Paper 14874, University Library of Munich, Germany.
    8. Maximo Camacho, 2002. "Nonlinear stochastic trends and economic fluctuations," Computing in Economics and Finance 2002 274, Society for Computational Economics.
    9. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
    10. Valerie Herzberg & George Kapetanios & Simon Price, 2003. "Import prices and exchange rate pass-through: theory and evidence from the United Kingdom," Bank of England working papers 182, Bank of England.
    11. Randall E. Parker & Philip Rothman, 2004. "An Examination of the Asymmetric Effects of Money Supply Shocks in the Pre--World War I and Interwar Periods," Economic Inquiry, Western Economic Association International, vol. 42(1), pages 88-100, January.
    12. Peter Martey Addo, 2014. "Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input," Papers 1407.7738, arXiv.org.
    13. Nedeljkovic, Milan, 2008. "Testing for Smooth Transition Nonlinearity in Adjustments of Cointegrating Systems," The Warwick Economics Research Paper Series (TWERPS) 876, University of Warwick, Department of Economics.
    14. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    15. Camacho, Maximo, 2005. "Markov-switching stochastic trends and economic fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 135-158, January.
    16. Turuntseva, M. & Zyamalov, V., 2016. "Stock Markets under the Changing Terms of Trade," Journal of the New Economic Association, New Economic Association, vol. 31(3), pages 93-109.
    17. Jonathan B. Hill, 2005. "Causation Delays and Causal Neutralization up to Three Steps Ahead: The Money-Output Relationship Revisited," Econometrics 0503016, University Library of Munich, Germany, revised 23 Mar 2005.
    18. Jawadi Fredj & Koubaa Yousra, 2004. "Threshold Cointegration between Stock Returns : An application of STECM Models," Econometrics 0412001, University Library of Munich, Germany.

  151. Franses, Ph.H.B.F. & de Bruin, P., 1999. "Seasonal adjustment and the business cycle in unemployment," Econometric Institute Research Papers EI 9923-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2018. "The Shifting Seasonal Mean Autoregressive Model and Seasonality in the Central England Monthly Temperature Series, 1772-2016," CREATES Research Papers 2018-15, Department of Economics and Business Economics, Aarhus University.
    2. Siem Jan Koopman & Kai Ming Lee, 0000. "Seasonality with Trend and Cycle Interactions in Unobserved Components Models," Tinbergen Institute Discussion Papers 08-028/4, Tinbergen Institute.
    3. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    4. Dalibor Stevanovic & Stéphane Surprenant & Rachidi Kotchoni, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.

  152. Carsoule, F. & Franses, Ph.H.B.F., 1999. "Monitoring structural change in variance," Econometric Institute Research Papers EI 9925A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Chen, Zhanshou & Tian, Zheng, 2010. "Modified procedures for change point monitoring in linear models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 62-75.

  153. Fok, D. & Franses, Ph.H.B.F. & Cramer, J.S., 1999. "Ordered logit analysis for selectively sampled data," Econometric Institute Research Papers EI 9933/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Fidrmuc, J.P. & Roosenboom, P.G.J. & van Dijk, D.J.C., 2007. "When Do Managers Seek Private Equity Backing in Public-to-Private Transactions?," ERIM Report Series Research in Management ERS-2007-028-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Jacek Kotlowski, 2005. "Reaction functions of the Polish central bankers. A logit approach," Working Papers 18, Department of Applied Econometrics, Warsaw School of Economics.

  154. Franses, Ph.H.B.F., 1999. "How to deal with intercept and trend in pratical cointegration analysis?," Econometric Institute Research Papers EI 9904-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Judith Giles & Cara Williams, 2001. "Export-led growth: a survey of the empirical literature and some non-causality results. Part 2," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 9(4), pages 445-470.
    2. Paul Blackley, 2011. "Production Adjustments for Consumer Durables and the Great Moderation," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 39(3), pages 291-302, September.
    3. Marks, Daan, 2010. "Unity or diversity? On the integration and efficiency of rice markets in Indonesia, c. 1920-2006," Explorations in Economic History, Elsevier, vol. 47(3), pages 310-324, July.
    4. Kaili Shen & David Giles, 2006. "Rational exuberance at the mall: addiction to carrying a credit card balance," Applied Economics, Taylor & Francis Journals, vol. 38(5), pages 587-592.
    5. Zhang, YunQian, 2022. "Influence of stock market factors on the natural resources dependence for environmental change: Evidence from China," Resources Policy, Elsevier, vol. 77(C).
    6. Chad Stroomer & David E.A. Giles, 2003. "Income Convergence and trade Openness: Fuzzy Clustering and Time Series Evidence," Econometrics Working Papers 0304, Department of Economics, University of Victoria.
    7. M.G. Dekimpe & D.M. Hanssens, 2005. "Persistence Models and Marketing Strategy," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(5), pages 855-884.
    8. Jochmann Markus & Koop Gary, 2015. "Regime-switching cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 35-48, February.
    9. Judith Giles & Cara Williams, 2001. "Export-led growth: a survey of the empirical literature and some non-causality results. Part 1," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 9(3), pages 261-337.
    10. David E. A. Giles, 2001. "Output Convergence and International Trade: Time-Series and Fuzzy Clustering Evidence for New Zealand and Her Trading Partners, 1950-1992," Econometrics Working Papers 0102, Department of Economics, University of Victoria.
    11. Ruud H. Koning, 2004. "FinMetrics: analysis of financial data in S-PLUS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 283-290.
    12. Irfan Civcir, 2003. "Before the Fall, Was the Turkish Lira Overvalued?," Eastern European Economics, Taylor & Francis Journals, vol. 41(2), pages 69-99, March.
    13. Kenneth G. Stewart & Michael C. Webb, 2003. "Capital Taxation, Globalization, and International Tax Competition," Econometrics Working Papers 0301, Department of Economics, University of Victoria.
    14. Burhan Ahmad & Ole Gjølberg, 2015. "Are Pakistan’s Rice Markets Integrated Domestically and With the International Markets?," SAGE Open, , vol. 5(3), pages 21582440155, July.
    15. Millet, Kobe & Lamey, Lien & Van den Bergh, Bram, 2012. "Avoiding negative vs. achieving positive outcomes in hard and prosperous economic times," Organizational Behavior and Human Decision Processes, Elsevier, vol. 117(2), pages 275-284.
    16. André van Stel & Roy Thurik & Chantal Hartog & Simon Parker, 2010. "The two-way relationship between entrepreneurship and economic performance," Scales Research Reports H200822, EIM Business and Policy Research.
    17. Thomas, Hugh & Wang, Zhiqiang, 2004. "The integration of bank syndicated loan and junk bond markets," Journal of Banking & Finance, Elsevier, vol. 28(2), pages 299-329, February.
    18. Johann Burgstaller, 2002. "Are stock returns a leading indicator for real macroeconomic developments?," Economics working papers 2002-07, Department of Economics, Johannes Kepler University Linz, Austria.
    19. Poncela, Pilar & Senra, Eva, 2002. "Forecasting monthly us consumer price indexes through a disaggregated I(2) analysis," DES - Working Papers. Statistics and Econometrics. WS ws020301, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Elger Thomas & Binner Jane M., 2004. "The UK Household Sector Demand for Risky Money," The B.E. Journal of Macroeconomics, De Gruyter, vol. 4(1), pages 1-22, March.
    21. Aurelijus Dabušinskas, 2005. "Money and Prices in Estonia," Bank of Estonia Working Papers 2005-07, Bank of Estonia, revised 10 Nov 2005.
    22. Chew Lian Chua & Sarantis Tsiaplias, 2014. "A Bayesian Approach to Modelling Bivariate Time-Varying Cointegration and Cointegrating Rank," Melbourne Institute Working Paper Series wp2014n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    23. Christos P. Pappas & Christos T. Papadas, 2015. "Farm Production Costs, Producer Prices and Retail Food Prices in Greece: A Cointegration Analysis," Bulletin of Political Economy, Bulletin of Political Economy, vol. 9(2), pages 127-143, December.
    24. Lence, Sergio H. & Plastina, Alejandro, 2020. "An Empirical Investigation of Productivity Spillovers along the Agricultural Supply Chain," ISU General Staff Papers 202001010800001066, Iowa State University, Department of Economics.
    25. Niko Gobbin & Glenn Rayp, 2008. "Different ways of looking at old issues: a time-series approach to inequality and growth," Applied Economics, Taylor & Francis Journals, vol. 40(7), pages 885-895.
    26. Binner, Jane & Elger, Thomas, 2002. "The UK Personal Sector Demand for Risky Money," Working Papers 2002:9, Lund University, Department of Economics.
    27. Dekimpe, M.G. & Hanssens, D.M., 2003. "Persistence Modeling for Assessing Marketing Strategy Performance," ERIM Report Series Research in Management ERS-2003-088-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  155. Nick Taylor & Dick van Dijk & Philip Hans Franses & André Lucas, 1999. "SETS, Arbitrage Activity, and Stock Price Dynamics," Tinbergen Institute Discussion Papers 99-003/4, Tinbergen Institute.

    Cited by:

    1. Lekkos, Ilias & Milas, Costas, 2004. "Time-varying excess returns on UK government bonds: A non-linear approach," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 45-62, January.
    2. Gaul, Jürgen & Theissen, Erik, 2012. "A partially linear approach to modelling the dynamics of spot and futures prices," CFR Working Papers 13-01, University of Cologne, Centre for Financial Research (CFR).
    3. Canto, Bea & Kräussl, Roman, 2007. "Electronic trading systems and intraday non-linear dynamics: An examination of the FTSE 100 cash and futures returns," CFS Working Paper Series 2007/20, Center for Financial Studies (CFS).
    4. Chen, Shiyi & Chng, Michael T. & Liu, Qingfu, 2021. "The implied arbitrage mechanism in financial markets," Journal of Econometrics, Elsevier, vol. 222(1), pages 468-483.
    5. Chelley-Steeley, Patricia & Siganos, Antonios, 2008. "Momentum profits in alternative stock market structures," Journal of Multinational Financial Management, Elsevier, vol. 18(2), pages 131-144, April.
    6. Chelley-Steeley, Patricia L., 2008. "Market quality changes in the London Stock Market," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2248-2253, October.
    7. Angelidis, Timotheos & Andrikopoulos, Andreas, 2010. "Idiosyncratic risk, returns and liquidity in the London Stock Exchange: A spillover approach," International Review of Financial Analysis, Elsevier, vol. 19(3), pages 214-221, June.
    8. Joseph K.W. Fung & Philip Yu, 2007. "Order Imbalance and the Dynamics of Index and Futures Prices," Working Papers 072007, Hong Kong Institute for Monetary Research.
    9. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    10. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    11. Yiuman Tse & Paramita Bandyopadhyay & Yang‐Pin Shen, 2006. "Intraday Price Discovery in the DJIA Index Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1572-1585, November.
    12. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    13. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    14. Wanbing Zhang & Sisi Zhang & Peibiao Zhao, 2019. "On Double Value at Risk," Risks, MDPI, vol. 7(1), pages 1-22, March.
    15. Assaf, Ata, 2006. "The stochastic volatility in mean model and automation: Evidence from TSE," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 241-253, May.
    16. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    17. Tse, Yiuman & Xiang, Ju, 2005. "Market quality and price discovery: Introduction of the E-mini energy futures," Global Finance Journal, Elsevier, vol. 16(2), pages 164-179, December.
    18. Robles-Fernandez M. Dolores & Nieto Luisa & Fernandez M. Angeles, 2004. "Nonlinear Intraday Dynamics in Eurostoxx50 Index Markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-28, December.
    19. Yiu‐Kuen Tse & Wai‐Sum Chan, 2010. "The Lead–Lag Relation Between The S&P500 Spot And Futures Markets: An Intraday‐Data Analysis Using A Threshold Regression Model," The Japanese Economic Review, Japanese Economic Association, vol. 61(1), pages 133-144, March.
    20. Juan A. Lafuente & Manuel Illueca Muñoz, 2003. "The Effect Of Futures Trading Activity On The Distribution Of Spot Market Returns," Working Papers. Serie EC 2003-23, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    21. Garrett Ian & Taylor Nicholas, 2001. "Intraday and Interday Basis Dynamics: Evidence from the FTSE 100 Index Futures Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(2), pages 1-22, July.
    22. Ivan Paya & David A. Peel, 2011. "Systematic sampling of nonlinear models: Evidence on speed of adjustment in index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 192-203, February.
    23. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    24. Charlie X. Cai & Robert Hudson & Kevin Keasey, 2004. "Intra Day Bid‐Ask Spreads, Trading Volume and Volatility: Recent Empirical Evidence from the London Stock Exchange," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 647-676, June.
    25. Stephen Norman, 2009. "Testing for a unit root against ESTAR nonlinearity with a delay parameter greater than one," Economics Bulletin, AccessEcon, vol. 29(3), pages 2152-2173.
    26. Christopher L. Gilbert & Herbert A. Rijken, 2006. "How is Futures Trading Affected by the Move to a Computerized Trading System? Lessons from the LIFFE FTSE 100 Contract," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(7‐8), pages 1267-1297, September.

  156. Fok, D. & Franses, Ph.H.B.F., 1999. "Impulse-response analysis of the market share attraction model," Econometric Institute Research Papers EI 9955-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

  157. Kleibergen, F.R. & Franses, Ph.H.B.F., 1999. "Cointegration in a periodic vector autoregression," Econometric Institute Research Papers EI 9906-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.

  158. Clements, M.P. & Franses, Ph.H.B.F. & Smith, J., 1999. "On SETAR non- linearity and forecasting," Econometric Institute Research Papers EI 9914-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    2. Frédérique Bec & Othman Bouabdallah & Laurent Ferrara, 2014. "The way out of recessions: A forecasting analysis for some Euro area countries," Post-Print hal-02979744, HAL.
    3. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    4. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," LIDAM Discussion Papers CORE 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. GIOT, Pierre & PETITJEAN, Mikael, 2007. "The information content of the Bond-Equity Yield Ratio: Better than a random walk?," LIDAM Reprints CORE 1982, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
    7. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    8. Costas Milas & Ruthira Naraidoo, 2009. "Financial Market Conditions, Real Time, Nonlinearity and European Central Bank Monetary Policy: In-Sample and Out-of-Sample Assessment," Working Paper series 42_09, Rimini Centre for Economic Analysis.
    9. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
    10. Bob Nobay & Ivan Paya & David A. Peel, 2010. "Inflation Dynamics in the U.S.: Global but Not Local Mean Reversion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 135-150, February.
    11. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
    12. Hui Feng & Jia Liu, 2002. "A SETAR Model for Canadian GDP: Non-Linearities and Forecast Comparisons," Econometrics Working Papers 0206, Department of Economics, University of Victoria.
    13. Frédérique Bec & Annabelle de Gaye, 2019. "Le modèle autorégressif autorégressif à seuil avec effet rebond : Une application aux rendements boursiers français et américains ," Working Papers hal-02014663, HAL.
    14. Asmara Jamaleh, 2002. "Explaining and forecasting the euro/dollar exchange rate through a non-linear threshold model," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 422-448.
    15. Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
    16. Frédérique Bec & Othman Bouabdallah & Laurent Ferrara, 2011. "The European Way Out of Recessions," THEMA Working Papers 2011-23, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    17. Ramazan Gencay & Ege Yazgan, 2017. "When Are Wavelets Useful Forecasters?," Working Papers 1704, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    18. Manzan, Sebastiano & Zerom, Dawit, 2008. "A bootstrap-based non-parametric forecast density," International Journal of Forecasting, Elsevier, vol. 24(3), pages 535-550.
    19. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Rodriguez, Nestor & Eales, James S., 2015. "Structural Change via Threshold Effects: Estimating U.S. Meat Demand Using Smooth Transition Functions and the Effects of More Women in the Labor Force," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206522, Agricultural and Applied Economics Association.
    21. Sánchez, Ismael, 2009. "Graphical identification of TAR models," DES - Working Papers. Statistics and Econometrics. WS ws097723, Universidad Carlos III de Madrid. Departamento de Estadística.
    22. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    23. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    24. Baik, Hyeoncheol & Han, Sumin & Joo, Sunghoon & Lee, Kangbok, 2022. "A bank's optimal capital ratio: A time-varying parameter model to the partial adjustment framework," Journal of Banking & Finance, Elsevier, vol. 142(C).
    25. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    26. de Morais, Igor Alexandre C. & Portugal, Marcelo Savino, 2005. "A Markov Switching Model for the Brazilian Demand for Imports: Analyzing the Import Substitution Process in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 25(2), November.
    27. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    28. Zacharias Psaradakis & Fabio Spagnolo, 2005. "Forecast performance of nonlinear error-correction models with multiple regimes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 119-138.
    29. Pedro M.D.C.B. Gouveia & Denise R. Osborn & Paulo M.M. Rodrigues, 2008. "Comparing Seasonal Forecasts of Industrial Production," Centre for Growth and Business Cycle Research Discussion Paper Series 102, Economics, The University of Manchester.
    30. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
    31. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Regime Switching and Artificial Neural Network Forecasting," Working Papers 0502, University of Crete, Department of Economics.

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    Cited by:

    1. López Villavicencio, Antonia, 2008. "Nonlinearities or outliers in real exchange rates?," Economic Modelling, Elsevier, vol. 25(4), pages 714-730, July.
    2. Samira Haddou, 2011. "Is Tunisian Real Effective Exchange Rate Mean Reverting? Evidence from Nonlinear Models," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 18(1), pages 164-178, September.

  160. Franses, Ph.H.B.F. & Ooms, M. & Bos, C.S., 1998. "Long memory and level shifts: re-analysing inflation rates," Econometric Institute Research Papers EI 9811, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
    2. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    3. Charles S. Bos & Philip Hans Franses & Marius Ooms, 2001. "Inflation, Forecast Intervals and Long Memory Regression Models," Tinbergen Institute Discussion Papers 01-029/4, Tinbergen Institute.
    4. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    5. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2014. "Are Labor Force Participation Rates Really Non-Stationary? Evidence from Three OECD Countries," Working Papers 15-25, Eastern Mediterranean University, Department of Economics.
    6. Nobay, A. Robert & Paya, Ivan & Peel, David A., 2007. "Inflation dynamics in the US - a nonlinear perspective," LSE Research Online Documents on Economics 24499, London School of Economics and Political Science, LSE Library.
    7. Gabriel Rodríguez & Dennis Alvaro & Ángel Guillén, 2016. "Modelling the Volatility of Commodities Prices using a Stochastic Volatility Model with Random Level Shifts," Documentos de Trabajo / Working Papers 2016-414, Departamento de Economía - Pontificia Universidad Católica del Perú.
    8. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    9. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    10. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    11. Claudio Morana, 2007. "A structural common factor approach to core inflation estimation and forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 163-169.
    12. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    13. Niels Haldrup & Morten O. Nielsen, 2004. "A Regime Switching Long Memory Model for Electricity Prices," Economics Working Papers 2004-2, Department of Economics and Business Economics, Aarhus University.
    14. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    15. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    16. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Long-memory dynamics in a SETAR model - Applications to stock markets," Post-Print halshs-00179339, HAL.
    17. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    18. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    19. Haldrup, Niels & Nielsen, Morten Oe., "undated". "Estimation of Fractional Integration in the Presence of Data Noise," Economics Working Papers 2003-10, Department of Economics and Business Economics, Aarhus University.
    20. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    21. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    22. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    23. Claudio Morana & Fabio Cesare Bagliano, 2007. "Inflation and monetary dynamics in the USA: a quantity-theory approach," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 229-244.
    24. L.A. Gil-Alana & G.M. caporale, 2004. "Long-run and Cyclical Dynamics in the US Stock Market," Econometric Society 2004 Latin American Meetings 344, Econometric Society.
    25. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    26. Morana, Claudio, 2000. "Measuring core inflation in the euro area," Working Paper Series 36, European Central Bank.
    27. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
    28. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    29. Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius, 2014. "Long memory with stochastic variance model: A recursive analysis for US inflation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 144-157.
    30. Heni Boubaker, 2016. "A Comparative Study of the Performance of Estimating Long-Memory Parameter Using Wavelet-Based Entropies," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 693-731, December.
    31. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
    32. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    33. Juncal Cunado & Luis Alberiko Gil-Alana & Fernando Perez de Gracia, 2008. "New Evidence on US Current Account Sustainability," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 1-21, April.
    34. McMillan, David G. & Wohar, Mark E., 2010. "Persistence and time-varying coefficients," Economics Letters, Elsevier, vol. 108(1), pages 85-88, July.
    35. Charles S. Bos, 2003. "Time Series Modelling using TSMod 3.24," Tinbergen Institute Discussion Papers 03-091/4, Tinbergen Institute.
    36. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2011. "International Labour Force Participation Rates by Gender: Unit Root or Structural Breaks?," ERC Working Papers 1105, ERC - Economic Research Center, Middle East Technical University, revised Oct 2011.
    37. Hyung, N. & Franses, Ph.H.B.F., 2002. "Inflation rates; long-memoray, level shifts, or both?," Econometric Institute Research Papers EI 2002-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    38. Reisen, Valdério Anselmo & Monte, Edson Zambon & da Conceição Franco, Glaura & Sgrancio, Adriano Marcio & Molinares, Fábio Alexander Fajardo & Bondon, Pascal & Ziegelmann, Flávio Augusto & Abraham, Bo, 2018. "Robust estimation of fractional seasonal processes: Modeling and forecasting daily average SO2 concentrations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 146(C), pages 27-43.
    39. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    40. Sibbertsen, Philipp & Wenger, Kai & Wingert, Simon, 2020. "Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series," Hannover Economic Papers (HEP) dp-676, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    41. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    42. Cleomar Gomes da Silva & Maria Carolina da Silva Leme, 2008. "Inflation and Interest Rate: Which one is more persistent in Brazil?," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807181224190, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    43. Hwang, Eunju & Shin, Dong Wan, 2013. "A CUSUM test for a long memory heterogeneous autoregressive model," Economics Letters, Elsevier, vol. 121(3), pages 379-383.
    44. Philip Hans Franses & Namwon Hyung, 2005. "Forecasting time series with long memory and level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 1-16.
    45. Guglielmo M. Caporale & Luis A. Gil‐Alana, 2004. "Testing for Seasonal Fractional Roots in German Real Output," German Economic Review, Verein für Socialpolitik, vol. 5(3), pages 319-333, August.
    46. Laura Mayoral, 2015. "The Persistence of Inflation in OECD Countries:a Fractionally Integrated Approach," Working Papers 259, Barcelona School of Economics.
    47. Vasco J. Gabriel & Luis F. Martins, 2000. "The Forecast Performance of Long Memory and Markov Switching Models," NIPE Working Papers 2/2000, NIPE - Universidade do Minho.
    48. Reisen Valderio A & Cribari-Neto Francisco & Jensen Mark J, 2003. "Long Memory Inflationary Dynamics: The Case of Brazil," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-18, October.
    49. Benjamin M. Tabak, 2007. "Estimating the Fractional Order of Integration of Yields in the Brazilian Fixed Income Market," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 36(3), pages 231-246, November.
    50. Choi, Kyongwook & Zivot, Eric, 2007. "Long memory and structural changes in the forward discount: An empirical investigation," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 342-363, April.
    51. G. K. Randolph TAN, 2004. "Long Memory in Import and Export Price Inflation and Persistence of Shocks to the Terms of Trade," Econometric Society 2004 Far Eastern Meetings 732, Econometric Society.
    52. Adnen Ben Nasr & Mohamed Boutahar & Abdelwahed Trabelsi, 2010. "Fractionally integrated time varying GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 399-430, August.
    53. Giorgio Canarella & Luis A. Gil-Alana & Rangan Gupta & Stephen M. Miller, 2020. "Modeling US historical time-series prices and inflation using alternative long-memory approaches," Empirical Economics, Springer, vol. 58(4), pages 1491-1511, April.
    54. Adnen Ben Nasr & Ahdi Noomen Ajmi & Rangan Gupta, 2014. "Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model," Applied Financial Economics, Taylor & Francis Journals, vol. 24(14), pages 993-1004, July.
    55. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    56. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    57. Morana Claudio, 2002. "Common Persistent Factors in Inflation and Excess Nominal Money Growth and a New Measure of Core Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-40, November.
    58. Baillie, Richard T. & Cho, Dooyeon & Rho, Seunghwa, 2024. "Combining Long and Short Memory in Time Series Models: the Role of Asymptotic Correlations of the MLEs," Econometrics and Statistics, Elsevier, vol. 29(C), pages 88-112.
    59. Georgios KOURETAS & Mark E. WOHAR, 2010. "The Dynamics of Inflation: A Study of a Large Number of Countries," EcoMod2010 259600096, EcoMod.
    60. Haldrup Niels & Nielsen Morten Ø., 2006. "Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-24, September.
    61. de Figueiredo, Erik Alencar, 2010. "Dynamics of regional unemployment rates in Brazil: Fractional behavior, structural breaks, and Markov switching," Economic Modelling, Elsevier, vol. 27(5), pages 900-908, September.
    62. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    63. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    64. Richard Paap & Philip Hans Franses & Marco Van Der Leij, 2002. "Modelling and forecasting level shifts in absolute returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 601-616.
    65. Chih-Chiang Hsu, 2000. "Long Memory or Structural Change: Testing Method and Empirical Examination," Econometric Society World Congress 2000 Contributed Papers 0867, Econometric Society.
    66. Conrad Christian & Karanasos Menelaos, 2005. "Dual Long Memory in Inflation Dynamics across Countries of the Euro Area and the Link between Inflation Uncertainty and Macroeconomic Performance," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-38, December.
    67. Luis A. Gil-Alana & Andrea Mervar & James E. Payne, 2017. "The stationarity of inflation in Croatia: anti-inflation stabilization program and the change in persistence," Economic Change and Restructuring, Springer, vol. 50(1), pages 45-58, February.
    68. Hwang, Eunju & Shin, Dong Wan, 2015. "A CUSUMSQ test for structural breaks in error variance for a long memory heterogeneous autoregressive model," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 167-176.
    69. Baillie Richard T. & Kapetanios George, 2016. "On the estimation of short memory components in long memory time series models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 365-375, September.
    70. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
    71. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2021. "Long-memory modeling and forecasting: evidence from the U.S. historical series of inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 289-310, December.
    72. Franses, Philip Hans & Janssens, Eva, 2018. "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 261-292.
    73. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "The effects of sovereign rating drifts on financial return distributions: Evidence from the European Union," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 5-20.
    74. Luis A. Gil-Alana & Yadollah Dadgar & Rouhollah Nazari, 2019. "Iranian inflation: peristence and structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 398-408, April.
    75. Narayan, Paresh Kumar & Popp, Stephan, 2011. "An application of a new seasonal unit root test to inflation," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 707-716, October.

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    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2004. "Non-Linearities And Fractional Integration In The Us Unemployment Rate," Public Policy Discussion Papers 04-17, Economics and Finance Section, School of Social Sciences, Brunel University.

  162. Philip Hans Franses & Dick van Dijk & André Lucas, 1998. "Short Patches of Outliers, ARCH and Volatility Modeling," Tinbergen Institute Discussion Papers 98-057/4, Tinbergen Institute.

    Cited by:

    1. Carnero, María Ángeles, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Jose Luis Miralles-Marcelo & Jose Luis Miralles-Quiros & Maria del Mar Miralles-Quiros, 2010. "Intraday linkages between the Spanish and the US stock markets: evidence of an overreaction effect," Applied Economics, Taylor & Francis Journals, vol. 42(2), pages 223-235.
    4. Amado Peir, 2016. "Changes in the Unconditional Variance and Autoregressive Conditional Heteroscedasticity," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1338-1343.
    5. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, January.
    6. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    7. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    8. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    9. Miralles-Quirós, José Luis & Daza-Izquierdo, Julio, 2015. "Do DOW returns really influence the intraday Spanish stock market behavior?," Research in International Business and Finance, Elsevier, vol. 33(C), pages 99-126.
    10. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    11. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    12. Par Sjolander, 2009. "Are the Basel II requirements justified in the presence of structural breaks?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(12), pages 985-998.
    13. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    14. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
    15. Par Sjolander, 2010. "A stationary unbiased finite sample ARCH-LM test procedure," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 1019-1033.
    16. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    17. Juncal Cunado Eizaguirre & Javier Gomez Biscarri & Fernando Perez de Gracia Hidalgo, 2009. "Financial liberalization, stock market volatility and outliers in emerging economies," Applied Financial Economics, Taylor & Francis Journals, vol. 19(10), pages 809-823.
    18. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
    19. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.

  163. Franses, Ph.H.B.F. & Paap, R., 1998. "Censored latent effects autoregression, with an application to US unemployment," Econometric Institute Research Papers EI 9841, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Paap, R. & Franses, Ph.H.B.F., 1999. "Do the US and Canada have a common nonlinear cycle in unemployment?," Econometric Institute Research Papers EI 9907-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  164. de Bruin, P. & Franses, Ph.H.B.F., 1998. "On data transformations and evidence of nonlinearity," Econometric Institute Research Papers EI 9823, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Philip Hans & de Bruin, Paul, 2002. "On data transformations and evidence of nonlinearity," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 621-632, September.
    2. Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
    3. Paul De Bruin & Philip Hans Franses, 1999. "Forecasting power-transformed time series data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(7), pages 807-815.

  165. Franses, Ph.H.B.F. & Neele, J. & van Dijk, D.J.C., 1998. "Forecasting volatility with switching persistence GARCH models," Econometric Institute Research Papers EI 9819, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    2. Mohamed El Hedi Arouri & Fredj Jawadi & Duc Khuong Nguyen, 2012. "Nonlinearities in carbon spot-futures price relationships during Phase II of the EU ETS," Post-Print hal-01410551, HAL.
    3. Gilles DUFRENOT & Laurent MATHIEU & Val=E9rie MIGNON & Anne PEGUIN-FEISSOLE, 2003. "Persistent misalignments of the European exchanges rates: some evidence from nonlinear cointegration," International Finance 0309003, University Library of Munich, Germany.
    4. Eskandar A. Tooma, 2003. "Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits," Working Papers 0310, Economic Research Forum, revised Apr 2003.
    5. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    6. Felix Chan & Michael McAleer, 2003. "Estimating smooth transition autoregressive models with GARCH errors in the presence of extreme observations and outliers," Applied Financial Economics, Taylor & Francis Journals, vol. 13(8), pages 581-592.
    7. Mohamed Chikhi & Claude Diebolt, 2019. "Testing Nonlinearity through a Logistic Smooth Transition AR Model with Logistic Smooth Transition GARCH Errors," Working Papers 03-19, Association Française de Cliométrie (AFC).
    8. Felix Chan & Michael McAleer, 2002. "Maximum likelihood estimation of STAR and STAR-GARCH models: theory and Monte Carlo evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 509-534.

  166. Franses, Ph.H.B.F. & Kunst, R.M., 1998. "On the role of seasonal intercepts in seasonal cointegration," Econometric Institute Research Papers EI 9820, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Johansen, S. & Schaumburg, E., 1997. "Likelihood Analysis of Seasonal Cointegration," Economics Working Papers eco97/16, European University Institute.
    2. Cubadda, Gianluca & Omtzigt, Pieter, 2003. "Small Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems," Economics & Statistics Discussion Papers esdp03012, University of Molise, Department of Economics.
    3. Agnieszka Tłuczak, 2022. "Convergence of prices on the pig market in selected European Union countries. Case study," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(3), pages 107-115.
    4. Franses, Philip Hans & Kunst, Robert M., 2007. "Analyzing a panel of seasonal time series: Does seasonality in industrial production converge across Europe?," Economic Modelling, Elsevier, vol. 24(6), pages 954-968, November.
    5. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    6. Lee, H.S. & Siklos, P.L., 1997. "The Role of Seasonality in Economic Time Series: Reinterpretating Money-Output Causality in U.S. Data," Working Papers 97-1, Wilfrid Laurier University, Department of Economics.
    7. Robert M. Kunst & Philip Hans Franses, 2011. "Testing for Seasonal Unit Roots in Monthly Panels of Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(4), pages 469-488, August.
    8. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Mårten Löf & Johan Lyhagen, 2003. "On seasonal error correction when the processes include different numbers of unit roots," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 377-389.
    10. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.
    11. Löf, Mårten & Lyhagen, Johan, 1999. "Forecasting performance of seasonal cointegration models," SSE/EFI Working Paper Series in Economics and Finance 336, Stockholm School of Economics.
    12. Gil-Alana, L.A., 2008. "Testing of seasonal integration and cointegration with fractionally integrated techniques: An application to the Danish labour demand," Economic Modelling, Elsevier, vol. 25(2), pages 326-339, March.
    13. Cellini, Roberto & Cuccia, Tiziana, 2009. "Museum and monument attendance and tourism flow: A time series analysis approach," MPRA Paper 18908, University Library of Munich, Germany.
    14. Reimers, Hans-Eggert, 1997. "Forecasting of seasonal cointegrated processes," International Journal of Forecasting, Elsevier, vol. 13(3), pages 369-380, September.
    15. Kunst, Robert M., 2009. "A Nonparametric Test for Seasonal Unit Roots," Economics Series 233, Institute for Advanced Studies.
    16. Gianluca Cubadda, 2000. "Complex Reduced Rank Models for Seasonally Cointegrated Time Series," Econometric Society World Congress 2000 Contributed Papers 0092, Econometric Society.
    17. Gianluca Cubadda, 2001. "Common Features In Time Series With Both Deterministic And Stochastic Seasonality," Econometric Reviews, Taylor & Francis Journals, vol. 20(2), pages 201-216.
    18. Helmut Herwartz & Hans-Eggert Reimers, 2003. "Seasonal cointegration analysis for German M3 money demand," Applied Financial Economics, Taylor & Francis Journals, vol. 13(1), pages 71-78.
    19. Justyna Wr'oblewska, 2020. "Bayesian analysis of seasonally cointegrated VAR model," Papers 2012.14820, arXiv.org, revised Apr 2021.
    20. Seong, Byeongchan, 2009. "Bonferroni correction for seasonal cointegrating ranks," Economics Letters, Elsevier, vol. 103(1), pages 42-44, April.
    21. Jacek Kotlowski, 2005. "Money and prices in the Polish economy. Seasonal cointegration approach," Working Papers 20, Department of Applied Econometrics, Warsaw School of Economics.
    22. Robert M. Kunst & Michael Reutter, 2000. "Decisions on Seasonal Unit Roots," CESifo Working Paper Series 286, CESifo.

  167. Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Siem Jan Koopman & Marius Ooms, 2001. "Time Series Modelling of Daily Tax Revenues," Tinbergen Institute Discussion Papers 01-032/4, Tinbergen Institute.

  168. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Nonlinear Error-Correction Models for Interest Rates in The Netherlands," Econometric Institute Research Papers EI 9704-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Samuel S Jibao & Niek Schoeman & Ruthira Naraidoo, 2010. "Fiscal Regime Changes and the Sustainability of Fiscal Imbalance in South Africa: A Smooth Transition Error-Correction Approach," Working Papers 201023, University of Pretoria, Department of Economics.
    2. Gilles Dufrénot & Valérie Mignon, 2002. "La cointégration non linéaire : une note méthodologique," Économie et Prévision, Programme National Persée, vol. 155(4), pages 117-137.
    3. Mark J. Holmes & Ping Wang, 2005. "Do African Countries Move Asymmetrically Towards Purchasing Power Parity?," South African Journal of Economics, Economic Society of South Africa, vol. 73(2), pages 292-301, June.
    4. Jerry Coakley & Ana-Maria Fuertes, 2001. "Nonparametric cointegration analysis of real exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 11(1), pages 1-8.
    5. Jerry Coakley & Ana-Maria Fuertes, 2002. "Asymmetric dynamics in UK real interest rates," Applied Financial Economics, Taylor & Francis Journals, vol. 12(6), pages 379-387.
    6. Roberto Golinelli, 1998. "Fatti stilizzati e metodi econometrici "moderni": una rivisitazione della curva di Phillips per l'Italia (1951-1996)," Politica economica, Società editrice il Mulino, issue 3, pages 411-446.
    7. Holmes, Mark J. & Maghrebi, Nabil, 2006. "Are international real interest rate linkages characterized by asymmetric adjustments?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(4), pages 384-396, October.
    8. R. Golinelli, 1998. "Fatti stilizzati e metodi econometrici "Moderni": una rivalutazione della Curva di Phillips per l'Italia (1951-1996)," Working Papers 313, Dipartimento Scienze Economiche, Universita' di Bologna.

  169. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Modelling Multiple Regimes in the Business Cycle," Econometric Institute Research Papers EI 9734/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    1. Cengiz, Sibel & Sahin, Afsin, 2013. "Modelling Nonlinear Behavior of Labor Force Participation Rate by STAR: An Application for Turkey," MPRA Paper 47805, University Library of Munich, Germany, revised 07 May 2013.
    2. Barbara Annicchiarico & Anna Rita Bennato & Emilio Zanetti Chini, 2014. "150 Years of Italian CO2 Emissions and Economic Growth," CEIS Research Paper 320, Tor Vergata University, CEIS, revised 31 Jul 2014.
    3. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, University Library of Munich, Germany, revised 05 Aug 2005.
    4. Rickard Sandberg, 2016. "Testing for unit roots in nonlinear heterogeneous panels with smoothly changing trends: an application to Scandinavian unemployment rates," Empirical Economics, Springer, vol. 51(3), pages 1053-1083, November.
    5. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    6. Jiangze Du & Shaojie Lai & Kin Keung Lai & Shifei Zhou, 2021. "A novel term structure stochastic model with adaptive correlation for trend analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5485-5498, October.
    7. Simeon Coleman & Juan C. Cuestas & Estefania Mourelle, 2012. "Investigating the oil price exchange rate nexus: evidence from Africa," NCID Working Papers 03/2012, Navarra Center for International Development, University of Navarra.
    8. Caggiano, Giovanni & Castelnuovo, Efrem & Groshenny, Nicolas, 2014. "Uncertainty shocks and unemployment dynamics in U.S. recessions," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 78-92.
    9. Samira Haddou, 2010. "Non-linéarité de la fonction de réaction des autorités monétaires tunisiennes," Économie et Prévision, Programme National Persée, vol. 195(4), pages 99-110.
    10. Jiang, Yu, 2020. "Identification of business cycles and the Great Moderation in the post-war U.S. economy," Economics Letters, Elsevier, vol. 190(C).
    11. David Guerreiro & Valérie Mignon, 2013. "On price convergence in Eurozone," Post-Print hal-01385859, HAL.
    12. Di Caro, Paolo, 2014. "Testing and explaining economic resilience with an application to Italian regions," MPRA Paper 60298, University Library of Munich, Germany.
    13. Jeremy Piger & James Morley & Chang-Jin Kim, 2005. "Nonlinearity and the permanent effects of recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 291-309.
    14. Honoré Sèwanoudé HOUNGBEDJI, 2022. "Non linéarité de la fonction de réaction de la Banque centrale des Etats de l’Afrique de l’Ouest," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 56, pages 133-157.
    15. Frédérique Bec & Othman Bouabdallah & Laurent Ferrara, 2014. "The way out of recessions: A forecasting analysis for some Euro area countries," Post-Print hal-02979744, HAL.
    16. Ubilava, David, 2016. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," Working Papers 2016-10, University of Sydney, School of Economics.
    17. Michael Arghyrou & Christopher Martin & Costas Milas, 2003. "Non-linear Inflationary Dynamics: Evidence from the UK," Public Policy Discussion Papers 03-03, Economics and Finance Section, School of Social Sciences, Brunel University.
    18. Faria, João Ricardo & Cuestas, Juan Carlos & Mourelle, Estefanía, 2010. "Entrepreneurship and unemployment: A nonlinear bidirectional causality?," Economic Modelling, Elsevier, vol. 27(5), pages 1282-1291, September.
    19. Gilles Dufrénot & Valérie Mignon, 2002. "La cointégration non linéaire : une note méthodologique," Économie et Prévision, Programme National Persée, vol. 155(4), pages 117-137.
    20. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    21. Valérie Mignon & Pauline Bucciarelli & Emmanuel Hache, 2024. "Evaluating criticality of strategic metals: Are the Herfindahl–Hirschman Index and usual concentration thresholds still relevant?," EconomiX Working Papers 2024-3, University of Paris Nanterre, EconomiX.
    22. Omar A Mendoza Lugo, 2008. "The differential impact of real interest rates and credit availability on private investment: evidence from Venezuela," BIS Papers chapters, in: Bank for International Settlements (ed.), Transmission mechanisms for monetary policy in emerging market economies, volume 35, pages 501-537, Bank for International Settlements.
    23. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    24. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    25. Ahmad, Saad, 2016. "A multiple threshold analysis of the Fed's balancing act during the Great Moderation," Economic Modelling, Elsevier, vol. 55(C), pages 343-358.
    26. Panayiotis C. Andreou & Christodoulos Louca & Christos S. Savva, 2016. "Short-horizon event study estimation with a STAR model and real contaminated events," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 673-697, October.
    27. Gilles DUFRENOT & Laurent MATHIEU & Val=E9rie MIGNON & Anne PEGUIN-FEISSOLE, 2003. "Persistent misalignments of the European exchanges rates: some evidence from nonlinear cointegration," International Finance 0309003, University Library of Munich, Germany.
    28. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.
    29. Davinson Stev Abril Salcedo & Luis Fernando Melo Velandia & Daniel Parra Amado, 2015. "Impactos de los fenómenos climáticos sobre el precio de los alimentos en Colombia," Borradores de Economia 13648, Banco de la Republica.
    30. Carlo Altavilla & Luigi Landolfo, 2005. "Do central banks act asymmetrically? Empirical evidence from the ECB and the Bank of England," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 507-519.
    31. Mendoza Lugo, Omar & Pedauga, Luis Enrique, 2006. "Efecto transferencia (pass-through) del tipo de cambio en los precios de bienes y servicios en Venezuela [Exchange rate pass-through on prices of goods and services in Venezuela]," MPRA Paper 14874, University Library of Munich, Germany.
    32. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    33. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
    34. Rickard Sandberg, 2018. "Unit Root Testing in Multiple Smooth Break Models with Nonlinear Dynamics," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 942-952, November.
    35. Don Bredin & Stilianos Fountas & Christos Savva, 2021. "Is British Output Growth Related to its Uncertainty? Evidence using Eight Centuries of Data," Discussion Paper Series 2021_02, Department of Economics, University of Macedonia, revised Feb 2021.
    36. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    37. Andreas Röthig, 2009. "Microeconomic Risk Management and Macroeconomic Stability," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-01565-6, February.
    38. Lof, Matthijs, 2010. "Heterogeneity in Stock Pricing: A STAR Model with Multivariate Transition Functions," MPRA Paper 30520, University Library of Munich, Germany.
    39. Carlo Altavilla & Paul De Grauwe, 2005. "Non-Linearities in the Relation between the Exchange Rate and its Fundamentals," CESifo Working Paper Series 1561, CESifo.
    40. Röthig, Andreas & Chiarella, Carl, 2006. "Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36774, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    41. Switzer, Lorne N. & Picard, Alan, 2016. "Stock market liquidity and economic cycles: A non-linear approach," Economic Modelling, Elsevier, vol. 57(C), pages 106-119.
    42. Balagtas, Joseph Valdes & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    43. Diggle, Paul & Bartholomew, Luke, 2022. "'Stall Speed' and 'Escape Velocity': Empty Metaphors or Empirical Realities?," CEPR Discussion Papers 14290, C.E.P.R. Discussion Papers.
    44. Kushal Banik Chowdhury & Nityananda Sarkar, 2019. "Regime Dependent Effect Of Output Growth On Output Growth Uncertainty: Evidence From Oecd Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 257-282, July.
    45. Emilio Zanetti Chini, 2016. "Generalizing smooth transition autoregressions," DEM Working Papers Series 114, University of Pavia, Department of Economics and Management.
    46. David Ubilava, 2012. "Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 28(1), pages 29-41, January.
    47. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    48. Krauss, Christopher & Herrmann, Klaus & Teis, Stefan, 2015. "On the power and size properties of cointegration tests in the light of high-frequency stylized facts," FAU Discussion Papers in Economics 11/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    49. Mr. Kazim Kazimov & Mr. Kirk Hamilton & Mr. Rabah Arezki, 2011. "Resource Windfalls, Macroeconomic Stability and Growth: The Role of Political Institutions," IMF Working Papers 2011/142, International Monetary Fund.
    50. Kyriakos C. Neanidis & Christos S. Savva, 2010. "Macroeconomic Uncertainty, Inflation and Growth: Regime-Dependent Effects in the G7," Centre for Growth and Business Cycle Research Discussion Paper Series 145, Economics, The University of Manchester.
    51. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    52. Gorgi, P. & Koopman, S.J., 2023. "Beta observation-driven models with exogenous regressors: A joint analysis of realized correlation and leverage effects," Journal of Econometrics, Elsevier, vol. 237(2).
    53. Dufrenot, Gilles & Mignon, Valerie & Peguin-Feissolle, Anne, 2004. "Business cycles asymmetry and monetary policy: a further investigation using MRSTAR models," Economic Modelling, Elsevier, vol. 21(1), pages 37-71, January.
    54. Rabah Arezki & Klaus Deininger & Harris Selod, 2012. "What drives the global rush?," NCID Working Papers 02/2012, Navarra Center for International Development, University of Navarra.
    55. Zhang, Lingxiang, 2013. "Modeling China's inflation dynamics: An MRSTAR approach," Economic Modelling, Elsevier, vol. 31(C), pages 440-446.
    56. Gilles DUFRENOT & Val=E9rie MIGNON & Anne PEGUIN-FEISSOLE, 2003. "Business cycles asymmetry and monetary policy: a further investigatio= n=20 using MRSTAR models," Macroeconomics 0309002, University Library of Munich, Germany.
    57. Munehisa Kasuya, 2003. "Regime-Switching Approach to Monetary Policy Effects: Empirical Studies using a Smooth Transition Vector Autoregressive Model," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.
    58. José Cancelo & Estefanía Mourelle, 2005. "Modeling Cyclical Asymmetries in European Imports," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 11(2), pages 135-147, May.
    59. Nidhal Mgadmi & Slim Chaouachi & Wajdi Moussa & Azza Bejaoui, 2021. "Does the Tunisian Central Bank follow an augmented nonlinear Taylor rule?," SN Business & Economics, Springer, vol. 1(1), pages 1-15, January.
    60. Mubariz Hasanov & Aysen Arac & Funda Telatar, 2012. "Nonlinearity and Structural Stability in the Phillips Curve: Evidence from Turkey," Hacettepe University Department of Economics Working Papers 20123, Hacettepe University, Department of Economics.
    61. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    62. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    63. Marco Rubilar-González & Gabriel Pino, 2018. "Are Euro-Area expectations about recession phases effective to anticipate consequences of economic crises?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 141-161, June.
    64. Michael J. Dueker, 2006. "Using cyclical regimes of output growth to predict jobless recoveries," Review, Federal Reserve Bank of St. Louis, vol. 88(Mar), pages 145-154.
    65. Bradley, Michael D. & Jansen, Dennis W., 2004. "Forecasting with a nonlinear dynamic model of stock returns and industrial production," International Journal of Forecasting, Elsevier, vol. 20(2), pages 321-342.
    66. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004.
    67. Apergis, Nicholas, 2015. "Financial portfolio choice: Do business cycle regimes matter? Panel evidence from international household surveys," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 14-27.
    68. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    69. Cheng, Xu, 2015. "Robust inference in nonlinear models with mixed identification strength," Journal of Econometrics, Elsevier, vol. 189(1), pages 207-228.
    70. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    71. Craig, Lee A. & Holt, Matthew T., 2008. "Mechanical refrigeration, seasonality, and the hog-corn cycle in the United States: 1870-1940," Explorations in Economic History, Elsevier, vol. 45(1), pages 30-50, January.
    72. Jose Maria Fernandez-Crehuet & Luis Alberiko Gil-Alana & Cristina Martí Barco, 2020. "Unemployment and Fertility: A Long Run Relationship," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(3), pages 1177-1196, December.
    73. Christopher Martin & Michael Arghyrou & Costas Milas, 2004. "Nonlinear inflation dynamics: evidence from the UK," Money Macro and Finance (MMF) Research Group Conference 2003 59, Money Macro and Finance Research Group.
    74. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October.
    75. David N. DeJong & Hariharan Dharmarajan & Roman Liesenfeld & Jean-Francois Richard, 2008. "Exploiting Non-Linearities in GDP Growth for Forecasting and Anticipating Regime Changes," Working Paper 367, Department of Economics, University of Pittsburgh, revised Sep 2008.
    76. Ming Luo & Ruguo Fan & Yingqing Zhang, 2017. "A Study on China’s Urban Electricity Productivity Convergence with Spatial Smooth Transition Effect," Sustainability, MDPI, vol. 9(8), pages 1-18, August.
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    Cited by:

    1. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    2. Ermini, Luigi, 1998. "A Tale of Three Seasonal Adjustment Procedures: The Case of Sweden's GDP," SSE/EFI Working Paper Series in Economics and Finance 230, Stockholm School of Economics.
    3. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.

  171. Franses, Philip Hans & Lucas, André, 1997. "Outlier robust cointegration analysis," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Aparicio, Felipe M. & García, Ana, 2004. "A range unit root test," DES - Working Papers. Statistics and Econometrics. WS ws041104, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Lucas, Andre, 2000. "A Note on Optimal Estimation from a Risk-Management Perspective under Possibly Misspecified Tail Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 31-39, January.
    3. Arranz, Miguel A., 2000. "Outliers robust ECM cointegration test based on the trend components," DES - Working Papers. Statistics and Econometrics. WS 10142, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Colombier, Carsten, 2012. "Healthcare expenditure projections up to 2060," MPRA Paper 104919, University Library of Munich, Germany.
    5. Arranz, Miguel A., 1998. "Detrending procedures and cointegration testing: ECM tests under structural breaks," DES - Working Papers. Statistics and Econometrics. WS 4551, Universidad Carlos III de Madrid. Departamento de Estadística.

  172. Franses, Ph.H.B.F. & Kloek, T. & Lucas, A., 1996. "Outlier Robust Analysis of Market Share and Distribution Relations for Weekly Scanning Data," Econometric Institute Research Papers EI 9646-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.

  173. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for ARCH in the Presence of Additive Outliers," Econometric Institute Research Papers EI 9659-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Carnero, María Ángeles, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Doornik, Jurgen A. & Ooms, Marius, 2008. "Multimodality in GARCH regression models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 432-448.
    3. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    4. Robin L. Lumsdaine & Serena Ng, 1998. "Testing for ARCH in the Presence of a Possibly Misspecified Conditional Mean," Boston College Working Papers in Economics 370, Boston College Department of Economics.
    5. Maki, Daiki, 2015. "Wild bootstrap testing for cointegration in an ESTAR error correction model," Economic Modelling, Elsevier, vol. 47(C), pages 292-298.
    6. Daiki Maki & Yasushi Ota, 2019. "Robust tests for ARCH in the presence of the misspecified conditional mean: A comparison of nonparametric approches," Papers 1907.12752, arXiv.org, revised Sep 2019.
    7. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2018. "The Shifting Seasonal Mean Autoregressive Model and Seasonality in the Central England Monthly Temperature Series, 1772-2016," CREATES Research Papers 2018-15, Department of Economics and Business Economics, Aarhus University.
    8. E. Ruiz & M.A. Carnero & D. Pereira, 2004. "Effects of Level Outliers on the Identification and Estimation of GARCH Models," Econometric Society 2004 Australasian Meetings 21, Econometric Society.
    9. Bali, Rakesh & Guirguis, Hany, 2007. "Extreme observations and non-normality in ARCH and GARCH," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 332-346.
    10. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    11. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    12. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    13. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
    14. Fang, WenShwo & Miller, Stephen M., 2009. "Modeling the volatility of real GDP growth: The case of Japan revisited," Japan and the World Economy, Elsevier, vol. 21(3), pages 312-324, August.
    15. Anatolyev, Stanislav & Tarasyuk, Irina, 2015. "Missing mean does no harm to volatility!," Economics Letters, Elsevier, vol. 134(C), pages 62-64.
    16. Paulo M.M. Rodrigues & Antonio Rubia, 2010. "The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance," Working Papers w201011, Banco de Portugal, Economics and Research Department.
    17. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    18. Daiki Maki, 2015. "Wild bootstrap tests for unit root in ESTAR models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 475-490, September.
    19. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    20. You‐How Go & Jia‐Jun Teo & Kam Fong Chan, 2023. "The effectiveness of crude oil futures hedging during infectious disease outbreaks in the 21st century," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1559-1575, November.
    21. Cizek, P., 2007. "Efficient Robust Estimation of Time-Series Regression Models," Other publications TiSEM d76eb299-a6b2-4f5a-bb9f-a, Tilburg University, School of Economics and Management.
    22. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    23. Jinliang Li & Chihwa Kao & Wei David Zhang, 2010. "Bounded influence estimator for GARCH models: evidence from foreign exchange rates," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1437-1445.
    24. Li, Yushu & Shukur, Ghazi, 2009. "Testing for Unit Root against LSTAR model – wavelet improvements under GARCH distortion," Working Paper Series in Economics and Institutions of Innovation 184, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    25. Daiki Maki & Yasushi Ota, 2019. "Testing for time-varying properties under misspecified conditional mean and variance," Papers 1907.12107, arXiv.org, revised Aug 2019.
    26. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    27. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    28. Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    29. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    30. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    31. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    32. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2008. "Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 109, Economics, The University of Manchester.
    33. Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
    34. Vasiliki Chatzikonstanti & Michail Karoglou, 2022. "Can black swans be tamed with a flexible mean‐variance specification?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3202-3227, July.
    35. Xibin Zhang & Maxwell L. King, 2002. "Influence Diagnostics in GARCH Processes," Monash Econometrics and Business Statistics Working Papers 19/02, Monash University, Department of Econometrics and Business Statistics.
    36. Duchesne, Pierre, 2004. "On robust testing for conditional heteroscedasticity in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 227-256, June.
    37. Veiga, Helena, 2009. "Wavelet-based detection of outliers in volatility models," DES - Working Papers. Statistics and Econometrics. WS ws090403, Universidad Carlos III de Madrid. Departamento de Estadística.
    38. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    39. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    40. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.
    41. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    42. Lei Shi & Md. Mostafizur Rahman & Wen Gan & Jianhua Zhao, 2015. "Stepwise local influence in generalized autoregressive conditional heteroskedasticity models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 428-444, February.
    43. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    44. Dejan Živkov & Jovan Njegić & Mirela Momčilović & Ivan Milenković, 2016. "Exchange Rate Volatility and Uncovered Interest Rate Parity in the European Emerging Economies," Prague Economic Papers, Prague University of Economics and Business, vol. 2016(3), pages 253-270.
    45. Martha Cecilia García & Aura María Jalal & Luis Alfonso Garzón & Jorge Mario López, 2013. "Métodos para predecir índices Bursátiles," Revista Ecos de Economía, Universidad EAFIT, December.
    46. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    47. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    48. Franses, Ph.H.B.F. & van Dijk, D.J.C., 1997. "Do We Often Find ARCH Because Of Neglected Outliers?," Econometric Institute Research Papers EI 9706-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    49. Francesco Battaglia & Lia Orfei, 2005. "Outlier Detection And Estimation In NonLinear Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 107-121, January.
    50. Cízek, Pavel, 2011. "Semiparametrically weighted robust estimation of regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 774-788, January.
    51. Vanessa Berenguer Rico & Ines Wilms, 2018. "White heteroscedasticty testing after outlier removal," Economics Series Working Papers 853, University of Oxford, Department of Economics.
    52. Dilip M. Nachane, 2011. "Selected Problems in the Analysis of Nonstationary & Nonlinear Time Series," Journal of Quantitative Economics, The Indian Econometric Society, vol. 9(1), pages 1-17.
    53. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Post-Print hal-00771828, HAL.
    54. Marcelo Cunha Medeiros & Alvaro Veiga, 2004. "Modelling multiple regimes in financial volatility with a flexible coefficient GARCH model," Textos para discussão 486, Department of Economics PUC-Rio (Brazil).
    55. Xibin Zhang, 2004. "Assessment of Local Influence in GARCH Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 301-313, March.
    56. Burkhard Raunig, 2003. "Testing for Longer Horizon Predictability of Return Volatility with an Application to the German," Working Papers 86, Oesterreichische Nationalbank (Austrian Central Bank).
    57. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    58. Charles, Amélie & Darné, Olivier, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 167-180.
    59. Hotta, Luiz & Trucíos, Carlos, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    60. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    61. Fokianos, Konstantions & Fried, Roland, 2009. "Interventions in ingarch processes," Technical Reports 2009,11, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    62. Battaglia, Francesco, 2005. "Outliers in functional autoregressive time series," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 323-332, May.
    63. Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    64. Yaqoob, Tanzeela & Maqsood, Arfa, 2024. "The potency of time series outliers in volatile models: An empirical analysis of fintech, and mineral resources," Resources Policy, Elsevier, vol. 89(C).
    65. Bhaumik, S. & Karanasos, M. & Kartsaklas, A., 2016. "The informative role of trading volume in an expanding spot and futures market," Journal of Multinational Financial Management, Elsevier, vol. 35(C), pages 24-40.
    66. Daiki Maki & Yasushi Ota, 2021. "Testing for Time-Varying Properties Under Misspecified Conditional Mean and Variance," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1167-1182, April.
    67. Cizek, P., 2007. "Efficient Robust Estimation of Regression Models (Revision of DP 2006-08)," Other publications TiSEM e88ea267-ce68-4569-98c3-7, Tilburg University, School of Economics and Management.
    68. Carnero, María Ángeles, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    69. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2008. "Estimating and Forecasting GARCH Volatility in the Presence of Outiers," Working Papers. Serie AD 2008-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    70. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.

  174. Breitung, J. & Franses, P. H., 1996. "On Phillips-Perron Type Tests for Seasonal Unit Roots," SFB 373 Discussion Papers 1996,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. El Montasser, Ghassen, 2014. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 54920, University Library of Munich, Germany.
    2. Luis C. Nunes & Paulo M. M. Rodrigues, 2011. "On LM‐type tests for seasonal unit roots in the presence of a break in trend," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(2), pages 108-134, March.
    3. Politis, Dimitris, 2016. "HEGY test under seasonal heterogeneity," University of California at San Diego, Economics Working Paper Series qt2q4054kf, Department of Economics, UC San Diego.
    4. Del Barrio Castro, T & Rodrigues, PMM & Taylor, AMR, 2015. "Semi-Parametric Seasonal Unit Root Tests," Essex Finance Centre Working Papers 16807, University of Essex, Essex Business School.
    5. Rodrigues, Paulo M. M. & Taylor, A. M. Robert, 2004. "Alternative estimators and unit root tests for seasonal autoregressive processes," Journal of Econometrics, Elsevier, vol. 120(1), pages 35-73, May.
    6. El Montasser, Ghassen, 2012. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 45110, University Library of Munich, Germany, revised 04 Mar 2014.
    7. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    8. Shin, Dong Wan & Lee, Oesook, 2007. "Asymmetry and nonstationarity for a seasonal time series model," Journal of Econometrics, Elsevier, vol. 136(1), pages 89-114, January.
    9. Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2007. "Efficient tests of the seasonal unit root hypothesis," Journal of Econometrics, Elsevier, vol. 141(2), pages 548-573, December.
    10. Shin, Dong Wan & Oh, Man-Suk, 2000. "Semiparametric tests for seasonal unit roots based on a semiparametric feasible GLSE," Statistics & Probability Letters, Elsevier, vol. 50(3), pages 207-218, November.
    11. Smith, Richard J. & Robert Taylor, A. M., 2001. "Recursive and rolling regression-based tests of the seasonal unit root hypothesis," Journal of Econometrics, Elsevier, vol. 105(2), pages 309-336, December.
    12. Niels Haldrup & Antonio Montanés & Andreu Sanso, "undated". "Measurement Errors and Outliers in Seasonal Unit Root Testing," Economics Working Papers 2000-8, Department of Economics and Business Economics, Aarhus University.
    13. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
    14. Gregoir, Stephane, 2006. "Efficient tests for the presence of a pair of complex conjugate unit roots in real time series," Journal of Econometrics, Elsevier, vol. 130(1), pages 45-100, January.
    15. Hassler, Uwe & Rodrigues, Paulo M. M., 2009. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77565, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    16. Shin, Dong Wan & Oh, Man-Suk, 2004. "Fully modified semiparametric GLS estimation for regressions with nonstationary seasonal regressors," Journal of Econometrics, Elsevier, vol. 122(2), pages 247-280, October.
    17. Shin, Dong Wan, 2004. "Estimation of spectral density for seasonal time series models," Statistics & Probability Letters, Elsevier, vol. 67(2), pages 149-159, April.
    18. Bauer, Dietmar, 2019. "Periodic and seasonal (co-)integration in the state space framework," Economics Letters, Elsevier, vol. 174(C), pages 165-168.
    19. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.

  175. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Econometric Institute Research Papers EI 9622-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Nonlinear Error-Correction Models for Interest Rates in The Netherlands," Econometric Institute Research Papers EI 9704-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Matas-Mir, Antonio & Osborn, Denise R., 2004. "Does seasonality change over the business cycle? An investigation using monthly industrial production series," European Economic Review, Elsevier, vol. 48(6), pages 1309-1332, December.
    3. Maki, Daiki, 2015. "Wild bootstrap testing for cointegration in an ESTAR error correction model," Economic Modelling, Elsevier, vol. 47(C), pages 292-298.
    4. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2021. "Investigating the asymmetric impact of oil prices on GCC stock markets," Post-Print hal-03529868, HAL.
    5. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    6. Shelley, Gary & Wallace, Frederick, 2010. "Further evidence regarding nonlinear trend reversion of real GDP and the CPI," MPRA Paper 24962, University Library of Munich, Germany.
    7. Fok, D. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2003. "A multi-level panel smooth transition autoregression for US sectoral production," Econometric Institute Research Papers EI 2003-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    9. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    10. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    11. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2018. "Oil Prices and GCC Stock Markets: New Evidence from Smooth Transition Models," CESifo Working Paper Series 7072, CESifo.
    12. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for ARCH in the Presence of Additive Outliers," Econometric Institute Research Papers EI 9659-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    14. Daiki Maki, 2015. "Wild bootstrap tests for unit root in ESTAR models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 475-490, September.
    15. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    16. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    17. Daiki Maki & Yasushi Ota, 2019. "Testing for time-varying properties under misspecified conditional mean and variance," Papers 1907.12107, arXiv.org, revised Aug 2019.
    18. Hafsa Hina & Abdul Qayyum, 2015. "Re-estimation of Keynesian Model by Considering Critical Events and Multiple Cointegrating Vectors," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 54(2), pages 123-145.
    19. Mendoza Lugo, Omar & Pedauga, Luis Enrique, 2006. "Efecto transferencia (pass-through) del tipo de cambio en los precios de bienes y servicios en Venezuela [Exchange rate pass-through on prices of goods and services in Venezuela]," MPRA Paper 14874, University Library of Munich, Germany.
    20. Jesús Otero & Jeremy Smith, 2005. "The KPSS Test with Outliers," Computational Economics, Springer;Society for Computational Economics, vol. 26(3), pages 59-67, November.
    21. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    22. Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
    23. Dick van Dijk & Philip Hans Franses, 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 727-744, December.
    24. PREMINGER, Arie & FRANCK, Raphael, 2007. "Forecasting exchange rates: a robust regression approach," LIDAM Reprints CORE 1917, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Brannolte Cord & Kim Jeong-Ryeol & Hansen Gerd, 1999. "Nonlinear Error Correction Modeling in German Interest Rates / Ein nichtlineares Fehlerkorrekturmodell für die deutsche Zinsstruktur," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 219(3-4), pages 271-283, June.
    26. Yamin Ahmad & Stuart Glosser, 2007. "Searching for Nonlinearities in Real Exchange Rates?," Working Papers 09-01, UW-Whitewater, Department of Economics, revised Jan 2009.
    27. Chan Wai-Sum & Hung King-Chi, 2011. "On Robust Testing and Modelling of Threshold-Type Non-Linearity in ASEAN Foreign Exchange Markets," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 5(2), pages 1-16, July.
    28. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    29. Hina, Hafsa & Qayyum, Abdul, 2013. "Estimation of Keynesian Exchange Rate Model of Pakistan by Considering Critical Events and Multiple Cointegrating Vectors," MPRA Paper 52611, University Library of Munich, Germany.
    30. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.
    31. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    32. Marianne Sensier & Denise R. Osborn & Nadir Öcal, 2002. "Asymmetric Interest Rate Effects for the UK Real Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 315-339, September.
    33. Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
    34. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    35. Escribano, A. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 1998. "Nonlinearities and outliers: robust specification of STAR models," Econometric Institute Research Papers EI 9832, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    44. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2006. "Não Linearidade Nos Ciclos De Negócios: Modelo Auto-Regressivo “Smooth Transition” Para O Índice Geral De Produção Industrial Brasileiro E Bens De Capital," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 10, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    45. Hina, Hafsa & Qayyum, Abdul, 2015. "Exchange Rate Determination and Out of Sample Forecasting: Cointegration Analysis," MPRA Paper 61997, University Library of Munich, Germany.
    46. Jawadi, Fredj & Namouri, Hela & Ftiti, Zied, 2018. "An analysis of the effect of investor sentiment in a heterogeneous switching transition model for G7 stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 469-484.
    47. Pentti Saikkonen & Rickard Sandberg, 2016. "Testing for a Unit Root in Noncausal Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 99-125, January.
    48. Hirsch, Tristan & Rinke, Saskia, 2017. "Changes in Persistence in Outlier Contaminated Time Series," Hannover Economic Papers (HEP) dp-583, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    49. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.
    50. Daiki Maki & Yasushi Ota, 2021. "Testing for Time-Varying Properties Under Misspecified Conditional Mean and Variance," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1167-1182, April.
    51. NIDHALEDDINE BEN CHEIKH & SAMI BEN NACEUR & OUSSAMA KANAAN & Christophe RAULT, 2019. "Oil Prices and GCC Stock Markets: New Evidence from Vector Smooth Transition Models," LEO Working Papers / DR LEO 2697, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    52. Samira Haddou, 2011. "Is Tunisian Real Effective Exchange Rate Mean Reverting? Evidence from Nonlinear Models," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 18(1), pages 164-178, September.
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    54. Rinke, Saskia, 2016. "The Influence of Additive Outliers on the Performance of Information Criteria to Detect Nonlinearity," Hannover Economic Papers (HEP) dp-575, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    55. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    56. King Chi Hung & Siu Hung Cheung & Wai-Sum Chan & Li-Xin Zhang, 2009. "On a robust test for SETAR-type nonlinearity in time series analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 445-464.
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    1. Mayr, Johannes & Ulbricht, Dirk, 2015. "Log versus level in VAR forecasting: 42 million empirical answers—Expect the unexpected," Economics Letters, Elsevier, vol. 126(C), pages 40-42.
    2. Wieringa, Jaap E. & Horvath, Csilla, 2005. "Computing level-impulse responses of log-specified VAR systems," International Journal of Forecasting, Elsevier, vol. 21(2), pages 279-289.
    3. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
    4. Bårdsen, Gunnar & Lütkepohl, Helmut, 2011. "Forecasting levels of log variables in vector autoregressions," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1108-1115, October.
    5. E. A. Fedorova & D. D. Airapetyan & S. O. Musienko & D. O. Afanas’ev & F. Yu. Fedorov, 2018. "Influence of Import Substitution Policy on the Industrial Production Level in Russia: Sector-Specific Issues," Studies on Russian Economic Development, Springer, vol. 29(2), pages 167-173, March.
    6. Fok, Dennis & Franses, Philip Hans, 2001. "Forecasting market shares from models for sales," International Journal of Forecasting, Elsevier, vol. 17(1), pages 121-128.
    7. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    9. González-Rivera, Gloria & Luo, Yun, 2019. "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS 29054, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Laing, Andrew R. & Nolan, James F., 2009. "Price Dynamics and Market Structure in Transportation: For-Hire Grain Trucking Along the Alberta- Saskatchewan Border," 50th Annual Transportation Research Forum, Portland, Oregon, March 16-18, 2009 207599, Transportation Research Forum.
    11. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    12. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.
    13. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    14. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    15. Lo, Danny K. & Hall, Anthony D., 2015. "Resiliency of the limit order book," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 222-244.
    16. Holtrop, Niels & Wieringa, Jakob & Gijsenberg, Maarten & Stern, P., 2016. "Competitive reactions to personal selling," Research Report 16004-MARK, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    17. Salmanzadeh-Meydani, N. & Fatemi Ghomi, S.M.T., 2019. "The causal relationship among electricity consumption, economic growth and capital stock in Iran," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1230-1256.
    18. Cheick Kader M’baye, 2023. "Fertility, employment, and the demographic dividend in sub-Saharan African countries with incipient demographic transition: evidence from Mali," Journal of Population Research, Springer, vol. 40(2), pages 1-15, June.
    19. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    20. Vijay Viswanathan & Linda D. Hollebeek & Edward C. Malthouse & Ewa Maslowska & Su Jung Kim & Wei Xie, 2017. "The Dynamics of Consumer Engagement with Mobile Technologies," Service Science, INFORMS, vol. 9(1), pages 36-49, March.
    21. Helene Olsen & Harald Wieslander, 2020. "The Impact of Monetary Policy on Leading Variables for Financial Stability in Norway," Working Papers No 02/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

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    Cited by:

    1. Rolando Gonzales Martínez, 2012. "Baysian seasonal analysis with robust priors," Investigación & Desarrollo, Universidad Privada Boliviana, vol. 1(1), pages 88-93.
    2. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    3. Raimundo Soto, 2002. "Ajuste Estacional e Integración en Variables Macroeconómicas," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 39(116), pages 135-155.
    4. Artur C. B. da Silva Lopes & Antonio Montañés, 2004. "The Behavior of HEGY Tests for Quarterly Time Series with Seasonal Mean Shifts," Econometrics 0411010, University Library of Munich, Germany.
    5. Alexander Vosseler & Enzo Weber, 2017. "Bayesian analysis of periodic unit roots in the presence of a break," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3841-3862, August.
    6. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    8. Mickael Salabasis & Sune Karlsson, 2004. "Seasonality, Cycles and Unit Roots," Econometric Society 2004 Australasian Meetings 268, Econometric Society.
    9. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    10. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    11. Hassler, Uwe & Rodrigues, Paulo M. M., 2009. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77565, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Paap, Richard & Franses, Philip Hans & Hoek, Henk, 1997. "Mean shifts, unit roots and forecasting seasonal time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 357-368, September.
    13. Harvey, David I. & Leybourne, Stephen J. & Newbold, Paul, 2002. "Seasonal unit root tests with seasonal mean shifts," Economics Letters, Elsevier, vol. 76(2), pages 295-302, July.

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    1. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.

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    1. Clements, Michael & Smith, Jeremy, 1997. "Forecasting Seasonal UK Consumption Components," The Warwick Economics Research Paper Series (TWERPS) 479, University of Warwick, Department of Economics.
    2. Smith, Jeremy & Otero, Jesus, 1995. "Structural Breaks and Seasonal Integration," Economic Research Papers 268653, University of Warwick - Department of Economics.
    3. Franses, Philip Hans & McAleer, Michael, 1997. "Testing periodically integrated autoregressive models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 457-465.
    4. Maekawa, Koichi, 1997. "Periodically integrated autoregression with a structural break," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 467-473.

  180. Franses, P.H. & Van Ieperen, R. & Kofman, P. & Martens, M. & Menkveld, B., 1994. "Volatility Patterns and Spillovers in Bund Futures," Monash Econometrics and Business Statistics Working Papers 16/94, Monash University, Department of Econometrics and Business Statistics.

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    1. Kaiser, Ulrich, 1997. "The determinants of BUND-future price changes: An ordered probit analysis using DTB and LIFFE data," ZEW Discussion Papers 97-09, ZEW - Leibniz Centre for European Economic Research.
    2. John Board & Charles Sutcliffe & Stephen Wells, 2002. "Transparency and Fragmentation," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-4039-0707-3, December.
    3. Franke, Günter & Hess, Dieter, 1995. "Anonymous electronic trading versus floor trading," Discussion Papers, Series II 285, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".

  181. Franses, P.H. & Boswijk, H.P., 1993. "Temporal aggregation in a periodically integrated autoregressive process," Research Memorandum FEW 599, Tilburg University, School of Economics and Management.

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    1. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    2. Rotger, Gabriel Pons, "undated". "Testing for Seasonal Unit Roots with Temporally Aggregated Time Series," Economics Working Papers 2003-16, Department of Economics and Business Economics, Aarhus University.
    3. Tilak Abeysinghe & Gulasekaran Rajaguru, 2004. "Temporal aggregation, causality distortions and a sign rule," Econometric Society 2004 Australasian Meetings 73, Econometric Society.
    4. Łukasz Lenart & Mateusz Pipień, 2015. "Empirical Properties of the Credit and Equity Cycle within Almost Periodically Correlated Stochastic Processes - the Case of Poland, UK and USA," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(3), pages 169-186, September.

  182. Franses, P.H. & Kofman, P., 1991. "An Empirical Test For Parities Between Metal Prices At The Ime," Papers 9102, Erasmus University of Rotterdam - Institute for Economic Research.

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    1. Richard Heaney, 1998. "A Test of the cost‐of‐carry relationship using the London Metal Exchange lead contract," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(2), pages 177-200, April.
    2. An-Sing Chen & James Wuh Lin, 2004. "Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract," Applied Economics, Taylor & Francis Journals, vol. 36(11), pages 1157-1167.
    3. Oscar Varela, 1999. "Futures and realized cash or settle prices for gold, silver, and copper," Review of Financial Economics, John Wiley & Sons, vol. 8(2), pages 121-138, September.
    4. Kim, MinKyoung & Koo, Won W., 2002. "How Differently Agricultural And Industrial Sectors Respond To Exchange Rate Fluctuation?," 2002 Annual meeting, July 28-31, Long Beach, CA 19635, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Clinton Watkins & Michael McAleer, 2004. "Econometric modelling of non‐ferrous metal prices," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 651-701, December.
    6. Riza Emekter & Benjamas Jirasakuldech & Peter Went, 2012. "Rational speculative bubbles and commodities markets: application of duration dependence test," Applied Financial Economics, Taylor & Francis Journals, vol. 22(7), pages 581-596, April.
    7. Guo, Jin, 2018. "Co-movement of international copper prices, China's economic activity, and stock returns: Structural breaks and volatility dynamics," Global Finance Journal, Elsevier, vol. 36(C), pages 62-77.
    8. Fernandez, Viviana & Pastén-Henríquez, Boris & Tapia-Griñen, Pablo & Wagner, Rodrigo, 2023. "Commodity prices under the threat of operational disruptions: Labor strikes at copper mines," Journal of Commodity Markets, Elsevier, vol. 32(C).
    9. Bildirici, Melike E. & Turkmen, Ceren, 2015. "Nonlinear causality between oil and precious metals," Resources Policy, Elsevier, vol. 46(P2), pages 202-211.
    10. Watkins, Clinton & McAleer, Michael, 2002. "Cointegration analysis of metals futures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(1), pages 207-221.

  183. Franses, P. H., 1990. "Seasonality, Nonstationarity And The Forecasting Of Monthly Time Series," Econometric Institute Archives 272481, Erasmus University Rotterdam.

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    1. Atle Oglend & Frank Asche, 2016. "Cyclical non-stationarity in commodity prices," Empirical Economics, Springer, vol. 51(4), pages 1465-1479, December.
    2. Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan, 2016. "Testing the historic tracking of climate models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1234-1246.
    3. Despotovic, Milan & Voyant, Cyril & Garcia-Gutierrez, Luis & Almorox, Javier & Notton, Gilles, 2024. "Solar irradiance time series forecasting using auto-regressive and extreme learning methods: Influence of transfer learning and clustering," Applied Energy, Elsevier, vol. 365(C).
    4. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    5. Mr. Manuk Ghazanchyan, 2014. "Unraveling the Monetary Policy Transmission Mechanism in Sri Lanka," IMF Working Papers 2014/190, International Monetary Fund.
    6. Michael Reutter & Jakob Von Weizsacker & Frank Westermann, 2002. "SeptemBear - A seasonality puzzle in the German stock index DAX," Applied Financial Economics, Taylor & Francis Journals, vol. 12(11), pages 765-769.
    7. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2003. "Nonlinear stochastic inflation modelling using SEASETARs," Insurance: Mathematics and Economics, Elsevier, vol. 32(1), pages 3-18, February.
    8. Gabriel Pino & J. D. Tena & Antoni Espasa, 2016. "Geographical disaggregation of sectoral inflation. Econometric modelling of the Euro area and Spanish economies," Applied Economics, Taylor & Francis Journals, vol. 48(9), pages 799-815, February.
    9. Sørensen, Nils Karl, 2002. "Modelling and seasonal forecasting of monthly hotel nights in Denmark," ERSA conference papers ersa02p114, European Regional Science Association.
    10. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    11. Martinez-Espineira, Roberto, 2005. "An Estimation of Residential Water Demand Using Co-Integration and Error Correction Techniques," MPRA Paper 615, University Library of Munich, Germany, revised Jan 2006.
    12. Tsui, Wai Hong Kan & Ozer Balli, Hatice & Gilbey, Andrew & Gow, Hamish, 2014. "Forecasting of Hong Kong airport's passenger throughput," Tourism Management, Elsevier, vol. 42(C), pages 62-76.
    13. Marco G. Ercolani & Jayasri Dutta, 2006. "The Euro-changeoverand Euro-inflation: Evidence from Eurostat's HICP," Discussion Papers 06-03, Department of Economics, University of Birmingham.
    14. Olivier Darné & Claude Diebolt, 2002. "A Note on Seasonal Unit Root Tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(3), pages 305-310, August.
    15. Carlos Fernández, 2001. "Further Evidence on Friedman's Hypothesis," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 38(115), pages 257-273.
    16. Song Shi & Martin Young & Bob Hargreaves, 2009. "The ripple effect of local house price movements in New Zealand," Journal of Property Research, Taylor & Francis Journals, vol. 26(1), pages 1-24, April.
    17. Chang, Chia-Lin & Sriboonchitta, Songsak & Wiboonpongse, Aree, 2009. "Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1730-1744.
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    19. Seamus McErlean & Ziping Wu & Joan Moss & Jos Ijpelaar & Andrew Doherty, 2003. "Do EU direct payments to beef producers belong in the ‘blue box’?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 47(1), pages 55-73, March.
    20. Antonio Aguirre, 2000. "Testing for seasonal unit roots using monthly data," Textos para Discussão Cedeplar-UFMG td139, Cedeplar, Universidade Federal de Minas Gerais.
    21. Juncal Cuñado & Luis A. Gil-Alaña, 2007. "Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models," Faculty Working Papers 02/07, School of Economics and Business Administration, University of Navarra.
    22. Jeong, Deokjae, 2022. "How the reduction of Temporary Foreign Workers led to a rise in vacancy rates in the South Korea," MPRA Paper 118731, University Library of Munich, Germany.
    23. Chang, C-L. & Khamkaew, T. & McAleer, M.J., 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," Econometric Institute Research Papers EI 2010-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    24. Song Shi & Martin Young & Bob Hargreaves, 2010. "House Price-Volume Dynamics: Evidence from 12 Cities in New Zealand," Journal of Real Estate Research, American Real Estate Society, vol. 32(1), pages 75-100.
    25. Budina, Nina & Maliszewski, Wojciech & de Menil, Georges & Turlea, Geomina, 2006. "Money, inflation and output in Romania, 1992-2000," Journal of International Money and Finance, Elsevier, vol. 25(2), pages 330-347, March.
    26. Waheed, Muhammad, 2007. "Central bank intervention, sterilization and monetary independence: the case of Pakistan," MPRA Paper 2328, University Library of Munich, Germany, revised Mar 2007.
    27. Rodrigues, P.M.M. & Franses, Ph.H.B.F., 2003. "A sequential approach to testing seasonal unit roots in high frequency data," Econometric Institute Research Papers EI 2003-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    28. M. Pulina, 2003. "Quantitative forecasting for Tourisme: OLS and ARIMAX approaches," Working Paper CRENoS 200303, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    29. Pino, Gabriel, 2008. "Forecasting Spanish inflation using information from different sectors and geographical areas," DES - Working Papers. Statistics and Econometrics. WS ws080101, Universidad Carlos III de Madrid. Departamento de Estadística.
    30. Luetkepohl Helmut & Xu Fang, 2011. "Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-23, February.
    31. Pino, Gabriel, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
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    36. Osborn, Denise R. & Heravi, Saeed & Birchenhall, C. R., 1999. "Seasonal unit roots and forecasts of two-digit European industrial production," International Journal of Forecasting, Elsevier, vol. 15(1), pages 27-47, February.
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    41. Syed Kalim Hyder Bukhari & Abdul Jalil & Nasir Hamid Rao, 2011. "Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited," SBP Working Paper Series 39, State Bank of Pakistan, Research Department.
    42. Yaovarate Chaovanapoonphol & Christine Lim & Michael McAleer & Aree Wiboonpongse, 2010. "Time Series Modelling of Tourism Demand from the USA, Japan and Malaysia to Thailand," Working Papers in Economics 10/05, University of Canterbury, Department of Economics and Finance.
    43. Albertson, Kevin & Aylen, Jonathan, 1996. "Modelling the Great Lakes freeze: forecasting and seasonality in the market for ferrous scrap," International Journal of Forecasting, Elsevier, vol. 12(3), pages 345-359, September.
    44. Jason B. Jorgensen & Fred Joutz, 2012. "Modelling and Forecasting Residential Electricity Consumption in the U.S. Mountain Region," Working Papers 2012-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    45. Otero, Jesús & Smith, Jeremy & Giulietti, Monica, 2008. "Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence," The Warwick Economics Research Paper Series (TWERPS) 865, University of Warwick, Department of Economics.
    46. Patrice Guillotreau & Frédéric Lantz & Lesya Nadzon & Jonathan Rault & Olivier Maury, 2023. "Price Transmission between Energy and Fish Markets: Are Oil Rates Good Predictors of Tuna Prices?," Marine Resource Economics, University of Chicago Press, vol. 38(1), pages 29-46.
    47. Wang, Lu & Wu, Rui & Ma, WeiChun & Xu, Weiju, 2023. "Examining the volatility of soybean market in the MIDAS framework: The importance of bagging-based weather information," International Review of Financial Analysis, Elsevier, vol. 89(C).
    48. Andres Silva & Senarath Dharmasena, 2016. "Considering seasonal unit root in a demand system: an empirical approach," Empirical Economics, Springer, vol. 51(4), pages 1443-1463, December.
    49. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    50. Julio César Alonso & Paul Seeman, 2010. "Prueba de HEGY en R: Una guía," Apuntes de Economía 9098, Universidad Icesi.
    51. Ramsey, James B. & Keenan, Sean, 1996. "Multi-country tests for the oscillator model with slowly varying coefficients," Journal of Economic Behavior & Organization, Elsevier, vol. 30(3), pages 383-408, September.
    52. Carlos Arnade & Daniel Pick, 1998. "Seasonality and unit roots: the demand for fruits," Agricultural Economics, International Association of Agricultural Economists, vol. 18(1), pages 53-62, January.
    53. Ankamah-Yeboah, Isaac, 2012. "Spatial Price Transmission in the Regional Maize Markets in Ghana," MPRA Paper 49720, University Library of Munich, Germany.
    54. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    55. Dulleck, Uwe & Kaufmann, Sylvia, 2004. "Do customer information programs reduce household electricity demand?--the Irish program," Energy Policy, Elsevier, vol. 32(8), pages 1025-1032, June.
    56. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    57. Nourani, Vahid & Sharghi, Elnaz & Behfar, Nazanin & Zhang, Yongqiang, 2022. "Multi-step-ahead solar irradiance modeling employing multi-frequency deep learning models and climatic data," Applied Energy, Elsevier, vol. 315(C).
    58. Garcia-Ferrer, A. & de Juan, A. & Poncela, P., 2006. "Forecasting traffic accidents using disaggregated data," International Journal of Forecasting, Elsevier, vol. 22(2), pages 203-222.
    59. Hans Franses, Philip & Koehler, Anne B., 1998. "A model selection strategy for time series with increasing seasonal variation," International Journal of Forecasting, Elsevier, vol. 14(3), pages 405-414, September.
    60. Sheng-Hung Chen & Song-Zan Chiou-Wei & Zhen Zhu, 2022. "Stochastic seasonality in commodity prices: the case of US natural gas," Empirical Economics, Springer, vol. 62(5), pages 2263-2284, May.
    61. Juan de Dios TENA & Antoni ESPASA & Gabriel PINO, 2010. "Forecasting Inflation and Relative Prices in the European Regions: A Case Study," Regional and Urban Modeling 284100040, EcoMod.
    62. Payman Eslami & Kihyo Jung & Daewon Lee & Amir Tjolleng, 2017. "Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 538-550, August.
    63. Lorde, Troy & Francis, Brian & Skeete, Stephney, 2008. "Are Shocks to Barbados Long-Stay Visitor Arrivals Permanent or Temporary: A Short Empirical Note," MPRA Paper 95597, University Library of Munich, Germany.
    64. Denise Osborn & Paulo Rodrigues, 2002. "Asymptotic Distributions Of Seasonal Unit Root Tests: A Unifying Approach," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 221-241.
    65. Michel Beine & Bertrand Candelon & Alain Hecq, 2000. "Assessing a Perfect European Optimum Currency Area: A Common Cycles Approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 27(2), pages 115-132, June.
    66. Hylleberg, Svend, 1995. "Tests for seasonal unit roots general to specific or specific to general?," Journal of Econometrics, Elsevier, vol. 69(1), pages 5-25, September.
    67. Florine Livat, 2007. "Mesure des interactions de prix : une analyse des modalités de substitution parmi sept vins de Bordeaux," Économie et Prévision, Programme National Persée, vol. 180(4), pages 127-145.
    68. Aruna Chandran & Ricardo Pérez-Núñez & Abdulgafoor M Bachani & Martha Híjar & Aarón Salinas-Rodríguez & Adnan A Hyder, 2014. "Early Impact of a National Multi-Faceted Road Safety Intervention Program in Mexico: Results of a Time-Series Analysis," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-7, January.

  184. Franses, P. H., 1990. "Testing For Seasonal Unit Roots In Monthly Data," Econometric Institute Archives 272393, Erasmus University Rotterdam.

    Cited by:

    1. Ana I. Sanjuán & Jose M. Gil, 2001. "A Note on Tests for Market Integration in a Multivariate Non‐Stationary Framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 52(2), pages 113-121, May.
    2. J. Joseph Beaulieu & Jeffrey A. Miron, 1992. "Seasonal Unit Roots in Aggregate U.S. Data," NBER Technical Working Papers 0126, National Bureau of Economic Research, Inc.
    3. Song Shi & Martin Young & Bob Hargreaves, 2009. "The ripple effect of local house price movements in New Zealand," Journal of Property Research, Taylor & Francis Journals, vol. 26(1), pages 1-24, April.
    4. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    5. Chang, Chia-Lin & Sriboonchitta, Songsak & Wiboonpongse, Aree, 2009. "Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1730-1744.
    6. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu & Kyophilavong, Phouphet, 2015. "Frequency domain causality analysis of stock market and economic activity in India," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 224-238.
    7. Syed Kumail Abbas Naqvi & Bushra Naqvi, 2010. "Asymmetric Behavior of Inflation Uncertainty and Friedman-Ball Hypothesis: Evidence from Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 15(2), pages 1-33, Jul-Dec.
    8. Franses, P. H., 1990. "Seasonality, Outliers And Linearity," Econometric Institute Archives 272395, Erasmus University Rotterdam.
    9. Song Shi & Martin Young & Bob Hargreaves, 2010. "House Price-Volume Dynamics: Evidence from 12 Cities in New Zealand," Journal of Real Estate Research, American Real Estate Society, vol. 32(1), pages 75-100.
    10. Broersma, L., 1991. "The relation between unemployment and interest rate : application of a seasonal Unit Root Test Procedure," Serie Research Memoranda 0068, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    11. Aviral Kumar Tiwari & Subhendu Dutta & Aruna Kumar Dash, 2017. "Testing of the Seasonal Unit Root Hypothesis in the Price Indices of Agricultural Commodities in India," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 14(2), pages 63-81, December.
    12. Leung, Charles Ka Yui & Shi, Song & Ho Tang, Edward Chi, 2013. "Commodity house prices," Regional Science and Urban Economics, Elsevier, vol. 43(6), pages 875-887.
    13. Ridderstaat, Jorge & Oduber, Marck & Croes, Robertico & Nijkamp, Peter & Martens, Pim, 2014. "Impacts of seasonal patterns of climate on recurrent fluctuations in tourism demand: Evidence from Aruba," Tourism Management, Elsevier, vol. 41(C), pages 245-256.
    14. Jason B. Jorgensen & Fred Joutz, 2012. "Modelling and Forecasting Residential Electricity Consumption in the U.S. Mountain Region," Working Papers 2012-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    15. Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2008. "Asymmetric Behavior of Inflation Uncertainty and Friedman-Ball Hypothesis: Evidence from Pakistan," MPRA Paper 19488, University Library of Munich, Germany.
    16. Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2009. "Inflation Volatility: An Asian Perspective," MPRA Paper 19489, University Library of Munich, Germany.
    17. Dario Cziráky & Max Gillman, 2006. "Money Demand in an EU Accession Country: A VECM Study of Croatia," Bulletin of Economic Research, Wiley Blackwell, vol. 58(2), pages 105-127, April.
    18. Tiwari, Aviral, 2010. "Is trade deficit sustainable in India? An inquiry," MPRA Paper 24451, University Library of Munich, Germany.
    19. Diaz-Emparanza, Ignacio, 2014. "Numerical distribution functions for seasonal unit root tests," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 237-247.
    20. Ashutosh Dash & Sangram Keshari Jena & Aviral Kumar Tiwari & Shawkat Hammoudeh, 2022. "Dynamics between Power Consumption and Economic Growth at Aggregated and Disaggregated (Sectoral) Level Using the Frequency Domain Causality," JRFM, MDPI, vol. 15(5), pages 1-18, May.
    21. Crowder, William J., 1996. "The international convergence of inflation rates during fixed and floating exchange rate regimes," Journal of International Money and Finance, Elsevier, vol. 15(4), pages 551-575, August.
    22. Reza Fazeli & Brynhildur Davidsdottir & Jonas Hlynur Hallgrimsson, 2016. "Climate Impact On Energy Demand For Space Heating In Iceland," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-23, May.

  185. Philip Hans Franses & Robert Taylor, "undated". "Determining the Order of Differencing in Seasonal Time Series Processes," Discussion Papers 97/9, Department of Economics, University of York.

    Cited by:

    1. Dillon Alleyne, 2006. "Can Seasonal Unit Root Testing Improve the Forecasting Accuracy of Tourist Arrivals?," Tourism Economics, , vol. 12(1), pages 45-64, March.
    2. Antonio Aguirre & Andreu Sansó, 2002. "Using different null hypotheses to test for seasonal unit roots in economic time series," Económica, Instituto de Investigaciones Económicas, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 3-26, January-D.
    3. Philip Hans Franses, 2005. "The Econometric Analysis of Seasonal Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 319-321, March.
    4. Josef Arlt, 2023. "The problem of annual inflation rate indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2772-2788, July.

Articles

  1. Mattera, Raffaele & Franses, Philip Hans, 2023. "Are African business cycles synchronized? Evidence from spatio-temporal modeling," Economic Modelling, Elsevier, vol. 128(C).

    Cited by:

    1. Caterina Morelli & Simone Boccaletti & Paolo Maranzano & Philipp Otto, 2024. "Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe," Papers 2405.20191, arXiv.org.

  2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    See citations under working paper version above.
  3. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.

  4. Philip Hans Franses, 2021. "Testing for bias in forecasts for independent binary outcomes," Applied Economics Letters, Taylor & Francis Journals, vol. 28(15), pages 1336-1338, September.

    Cited by:

    1. Philip Hans Franses & Richard Paap, 2025. "Testing for Bias in Forecasts for Independent Multinomial Outcomes," Forecasting, MDPI, vol. 7(1), pages 1-8, January.

  5. Philip Hans Franses, 2021. "Testing bias in professional forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1086-1094, September.

    Cited by:

    1. Carola Binder & Wesley Janson & Randal Verbrugge, 2023. "Out of Bounds: Do SPF Respondents Have Anchored Inflation Expectations?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(2-3), pages 559-576, March.

  6. Philip Hans Franses & Thomas Wiemann, 2020. "Intertemporal Similarity of Economic Time Series: An Application of Dynamic Time Warping," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 59-75, June.

    Cited by:

    1. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    2. Miljkovic, Dragan & Vatsa, Puneet, 2023. "On the linkages between energy and agricultural commodity prices: A dynamic time warping analysis," International Review of Financial Analysis, Elsevier, vol. 90(C).
    3. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    4. Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.
    5. Mattera, Raffaele & Franses, Philip Hans, 2023. "Are African business cycles synchronized? Evidence from spatio-temporal modeling," Economic Modelling, Elsevier, vol. 128(C).
    6. Tatsuru Kikuchi & Toranosuke Onishi & Kenichi Ueda, 2021. "Price Stability of Cryptocurrencies as a Medium of Exchange," Papers 2111.08390, arXiv.org.
    7. Xing, Zhuoqun & Pan, Yiqun & Yang, Yiting & Yuan, Xiaolei & Liang, Yumin & Huang, Zhizhong, 2024. "Transfer learning integrating similarity analysis for short-term and long-term building energy consumption prediction," Applied Energy, Elsevier, vol. 365(C).

  7. Philip Hans Franses, 2020. "Simple Bayesian Forecast Combination," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-7, December.

    Cited by:

    1. Juntao Li & Tianxu Cui & Kaiwen Yang & Ruiping Yuan & Liyan He & Mengtao Li, 2021. "Demand Forecasting of E-Commerce Enterprises Based on Horizontal Federated Learning from the Perspective of Sustainable Development," Sustainability, MDPI, vol. 13(23), pages 1-29, November.

  8. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.

    Cited by:

    1. Arbab Khalid Cheema & Wenjie Ding & Qingwei Wang, 2023. "The cross-section of January effect," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 513-530, October.
    2. Philip Hans Franses & Max Welz, 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," JRFM, MDPI, vol. 13(3), pages 1-8, March.

  9. Philip Hans Franses, 2020. "IMA(1,1) as a new benchmark for forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 27(17), pages 1419-1423, October.
    See citations under working paper version above.
  10. Gilian van den Hengel & Philip Hans Franses, 2020. "Forecasting Social Conflicts in Africa Using an Epidemic Type Aftershock Sequence Model," Forecasting, MDPI, vol. 2(3), pages 1-25, August.
    See citations under working paper version above.
  11. Dick van Dijk & Philip Hans Franses, 2019. "Combining expert‐adjusted forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(5), pages 415-421, August.

    Cited by:

    1. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    2. Anyu Liu & Laura Vici & Vicente Ramos & Sauveur Giannoni & Adam Blake, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team," Post-Print hal-04653783, HAL.
    3. Liu, Anyu & Vici, Laura & Ramos, Vicente & Giannoni, Sauveur & Blake, Adam, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team," Annals of Tourism Research, Elsevier, vol. 88(C).

  12. Philip Hans Franses, 2019. "On inflation expectations in the NKPC model," Empirical Economics, Springer, vol. 57(6), pages 1853-1864, December.

    Cited by:

    1. Choi, Yoonseok, 2021. "Inflation dynamics, the role of inflation at different horizons and inflation uncertainty," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 649-662.
    2. Ooft, G. & Bhaghoe, S. & Franses, Ph.H.B.F., 2019. "Forecasting Annual Inflation in Suriname," Econometric Institute Research Papers EI2019-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  13. Philip Hans Franses & Max Welz, 2019. "Cash Use of the Taiwan Dollar: Is It Efficient? †," JRFM, MDPI, vol. 12(1), pages 1-6, January.

    Cited by:

    1. Chia-Lin Chang, 2020. "Editorial for Applied Econometrics," JRFM, MDPI, vol. 13(9), pages 1-5, August.

  14. Philip Hans Franses & Eva Janssens, 2019. "Spurious principal components," Applied Economics Letters, Taylor & Francis Journals, vol. 26(1), pages 37-39, January.
    See citations under working paper version above.
  15. Franses, Philip Hans & Janssens, Eva, 2018. "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 261-292.

    Cited by:

    1. Franses, Ph.H.B.F., 2020. "An introduction to time-varying lag autoregression," Econometric Institute Research Papers EI2020-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  16. Bert De Bruijn & Philip Hans Franses, 2018. "How Informative Are Earnings Forecasts? †," JRFM, MDPI, vol. 11(3), pages 1-20, July.

    Cited by:

    1. Ching-Chih Wu & Tung-Hsiao Yang, 2018. "Insider Trading and Institutional Holdings in Seasoned Equity Offerings," JRFM, MDPI, vol. 11(3), pages 1-14, September.

  17. Philip Hans Franses & Rianne Legerstee & Richard Paap, 2017. "Estimating loss functions of experts," Applied Economics, Taylor & Francis Journals, vol. 49(4), pages 386-396, January.
    See citations under working paper version above.
  18. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Exploiting Spillovers to Forecast Crashes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 936-955, December.
    See citations under working paper version above.
  19. Philip Hans Franses & Eva Janssens, 2017. "Recovering Historical Inflation Data from Postage Stamps Prices," JRFM, MDPI, vol. 10(4), pages 1-11, November.
    See citations under working paper version above.
  20. Segers, Rene & Franses, Philip Hans & de Bruijn, Bert, 2017. "A novel approach to measuring consumer confidence," Econometrics and Statistics, Elsevier, vol. 4(C), pages 121-129.
    See citations under working paper version above.
  21. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Specification Testing in Hawkes Models," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 139-171.
    See citations under working paper version above.
  22. Bert De Bruijn & Philip Hans Franses, 2017. "Heterogeneous Forecast Adjustment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(4), pages 337-344, July.

    Cited by:

    1. Etienne Theising, 2024. "Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables," Papers 2405.03402, arXiv.org.
    2. Etienne Theising & Dominik Wied & Daniel Ziggel, 2023. "Reference class selection in similarity‐based forecasting of corporate sales growth," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1069-1085, August.

  23. Donkers, Bas & van Diepen, Merel & Franses, Philip Hans, 2017. "Do charities get more when they ask more often? Evidence from a unique field experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 66(C), pages 58-65.
    See citations under working paper version above.
  24. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2017. "Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 90-101.

    Cited by:

    1. Dai, Hongyan & Xiao, Qin & Chen, Songlin & Zhou, Weihua, 2023. "Data-driven demand forecast for O2O operations: An adaptive hierarchical incremental approach," International Journal of Production Economics, Elsevier, vol. 259(C).
    2. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2021. "Forecasting time-varying arrivals: Impact of direct response advertising on call center performance," Journal of Business Research, Elsevier, vol. 131(C), pages 227-240.

  25. Franses, Philip Hans, 2016. "A note on the Mean Absolute Scaled Error," International Journal of Forecasting, Elsevier, vol. 32(1), pages 20-22.

    Cited by:

    1. Kang, Yanfei & Spiliotis, Evangelos & Petropoulos, Fotios & Athiniotis, Nikolaos & Li, Feng & Assimakopoulos, Vassilios, 2021. "Déjà vu: A data-centric forecasting approach through time series cross-similarity," Journal of Business Research, Elsevier, vol. 132(C), pages 719-731.
    2. Miguel Ángel Echarte Fernández & Sergio Luis Náñez Alonso & Ricardo Reier Forradellas & Javier Jorge-Vázquez, 2022. "From the Great Recession to the COVID-19 Pandemic: The Risk of Expansionary Monetary Policies," Risks, MDPI, vol. 10(2), pages 1-17, January.
    3. Beltrán, Sergio & Castro, Alain & Irizar, Ion & Naveran, Gorka & Yeregui, Imanol, 2022. "Framework for collaborative intelligence in forecasting day-ahead electricity price," Applied Energy, Elsevier, vol. 306(PA).
    4. Jens Kley-Holsteg & Florian Ziel, 2020. "Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso," Papers 2005.04522, arXiv.org.
    5. Wen, Shizhao & Wang, Hongzeng & Qian, Jinhua & Men, Xuanyu, 2023. "A novel combined model based on echo state network optimized by whale optimization algorithm for blast furnace gas prediction," Energy, Elsevier, vol. 279(C).
    6. Rostami-Tabar, Bahman & Ziel, Florian, 2022. "Anticipating special events in Emergency Department forecasting," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1197-1213.
    7. Evangelos Spiliotis & Spyros Makridakis & Artemios-Anargyros Semenoglou & Vassilios Assimakopoulos, 2022. "Comparison of statistical and machine learning methods for daily SKU demand forecasting," Operational Research, Springer, vol. 22(3), pages 3037-3061, July.
    8. Francesco Lisi & Ismail Shah, 2024. "Joint Component Estimation for Electricity Price Forecasting Using Functional Models," Energies, MDPI, vol. 17(14), pages 1-18, July.
    9. Barkha Parkash & Tek Tjing Lie & Weihua Li & Shafiqur Rahman Tito, 2024. "End-to-End Top-Down Load Forecasting Model for Residential Consumers," Energies, MDPI, vol. 17(11), pages 1-20, May.
    10. Ogliari, Emanuele & Guilizzoni, Manfredo & Giglio, Alessandro & Pretto, Silvia, 2021. "Wind power 24-h ahead forecast by an artificial neural network and an hybrid model: Comparison of the predictive performance," Renewable Energy, Elsevier, vol. 178(C), pages 1466-1474.
    11. Chiang, Shu-Mei & Chen, Chun-Da & Huang, Chien-Ming, 2019. "Analyzing the impacts of foreign exchange and oil price on biofuel commodity futures," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 37-48.
    12. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
    13. Julio Barzola-Monteses & Mónica Mite-León & Mayken Espinoza-Andaluz & Juan Gómez-Romero & Waldo Fajardo, 2019. "Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case," Sustainability, MDPI, vol. 11(23), pages 1-19, November.
    14. David BENATIA, 2020. "Reaching New Lows? The Pandemic's Consequences for Electricity Markets," Working Papers 2020-12, Center for Research in Economics and Statistics.
    15. Jiangwei Liu & Xiaohong Huang, 2021. "Forecasting Crude Oil Price Using Event Extraction," Papers 2111.09111, arXiv.org.
    16. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    17. Montero-Sousa, Juan Aurelio & Aláiz-Moretón, Héctor & Quintián, Héctor & González-Ayuso, Tomás & Novais, Paulo & Calvo-Rolle, José Luis, 2020. "Hydrogen consumption prediction of a fuel cell based system with a hybrid intelligent approach," Energy, Elsevier, vol. 205(C).
    18. Krzysztof Tomczyk, 2023. "Extended Calibration of Charge Mode Accelerometers to Improve the Accuracy of Energy Systems," Energies, MDPI, vol. 16(22), pages 1-14, November.
    19. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    20. Monika Zimmermann & Florian Ziel, 2024. "Efficient mid-term forecasting of hourly electricity load using generalized additive models," Papers 2405.17070, arXiv.org.
    21. Ismail Shah & Francesco Lisi, 2020. "Forecasting of electricity price through a functional prediction of sale and purchase curves," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 242-259, March.
    22. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    23. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    24. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    25. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
    27. Pokorný, Jiří & Froněk, Pavel, 2021. "Price Forecasting Accuracy of the OECD-FAO's Agricultural Outlook and the European Commission DG AGRI's Medium-Term Agricultural Outlook Report," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 13(3), September.
    28. Nuri Hacıevliyagil & Krzysztof Drachal & Ibrahim Halil Eksi, 2022. "Predicting House Prices Using DMA Method: Evidence from Turkey," Economies, MDPI, vol. 10(3), pages 1-27, March.

  26. Franses, Philip Hans, 2016. "A simple test for a bubble based on growth and acceleration," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 160-169.

    Cited by:

    1. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    2. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2018. "Can bubble theory foresee banking crises?," Journal of Financial Stability, Elsevier, vol. 36(C), pages 66-81.
    3. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.

  27. Philip Hans Franses & Wouter Knecht, 2016. "The late 1970s bubble in Dutch collectible postage stamps," Empirical Economics, Springer, vol. 50(4), pages 1215-1228, June.
    See citations under working paper version above.
  28. Sanne Blauw & Philip Hans Franses, 2016. "Off the Hook: Measuring the Impact of Mobile Telephone Use on Economic Development of Households in Uganda using Copulas," Journal of Development Studies, Taylor & Francis Journals, vol. 52(3), pages 315-330, March.

    Cited by:

    1. Raksmey, Uch & Lin, Ching-Yang & Kakinaka, Makoto, 2022. "Macroprudential regulation and financial inclusion: Any difference between developed and developing countries?," Research in International Business and Finance, Elsevier, vol. 63(C).
    2. Sekabira, Haruna & Qaim, Matin, 2017. "Can Mobile Phones Improve Gender Equality and Nutrition? Panel Data Evidence from Farm Households in Uganda," GlobalFood Discussion Papers 256215, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    3. Sekabira, Haruna & Qaim, Matin, 2016. "Mobile Phone Technologies, Agricultural Production Patterns, and Market access in Uganda," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246310, African Association of Agricultural Economists (AAAE).
    4. Hong, Yan-Zhen & Chang, Hung-Hao, 2020. "Does digitalization affect the objective and subjective wellbeing of forestry farm households? Empirical evidence in Fujian Province of China," Forest Policy and Economics, Elsevier, vol. 118(C).
    5. Gershom Endelani Mwalupaso & Shangao Wang & Sanzidur Rahman & Essiagnon John-Philippe Alavo & Xu Tian, 2019. "Agricultural Informatization and Technical Efficiency in Maize Production in Zambia," Sustainability, MDPI, vol. 11(8), pages 1-17, April.
    6. Sekabira, Haruna & Qaim, Matin, 2016. "Mobile Money, Agricultural Marketing, and Off-Farm Income in Uganda," GlobalFood Discussion Papers 234998, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    7. Sekabira, Haruna & Qaim, Matin, 2017. "Can mobile phones improve gender equality and nutrition? Panel data evidence from farm households in Uganda," Food Policy, Elsevier, vol. 73(C), pages 95-103.
    8. Martha Jiménez García, 2019. "The Impact of Information and Communication Technologies on Economic Growth in Mexico," International Journal of Business and Social Research, LAR Center Press, vol. 9(2), pages 11-22, February.
    9. Kim, Namil & Kim, Wonjoon, 2018. "Do your social media lead you to make social deal purchases? Consumer-generated social referrals for sales via social commerce," International Journal of Information Management, Elsevier, vol. 39(C), pages 38-48.
    10. Hian Teck Hoon & Margarita Katsimi & Gylfi Zoega, 2023. "Investment and the long swings of unemployment," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(3), pages 611-632, July.
    11. Pelletier, Adeline & Khavul, Susanna & Estrin, Saul, 2019. "Innovations in emerging markets: the case of mobile money," LSE Research Online Documents on Economics 101150, London School of Economics and Political Science, LSE Library.
    12. Gupta, Suraksha & Kanungo, Rama Prasad, 2022. "Financial inclusion through digitalisation: Economic viability for the bottom of the pyramid (BOP) segment," Journal of Business Research, Elsevier, vol. 148(C), pages 262-276.
    13. Gershom Endelani Mwalupaso & Shangao Wang & Zhangxing Xu & Xu Tian, 2019. "Towards Auspicious Agricultural Informatization—Implication of Farmers’ Behavioral Intention Apropos of Mobile Phone Use in Agriculture," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    14. Lashitew, Addisu A. & van Tulder, Rob & Liasse, Yann, 2019. "Mobile phones for financial inclusion: What explains the diffusion of mobile money innovations?," Research Policy, Elsevier, vol. 48(5), pages 1201-1215.
    15. Francesco Billari & Jenny Trinitapoli & Valentina Rotondi, 2020. "Mobile phones, digital inequality, and fertility: Longitudinal evidence from Malawi," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(37), pages 1057-1096.

  29. Tina Dulam & Philip Hans Franses, 2015. "Emigration, wage differentials and brain drain: the case of Suriname," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2339-2347, May.
    See citations under working paper version above.
  30. Rianne Legerstee & Philip Hans Franses, 2015. "Does Disagreement Amongst Forecasters Have Predictive Value?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(4), pages 290-302, July.
    See citations under working paper version above.
  31. Philip Hans Franses, 2015. "The life cycle of social media," Applied Economics Letters, Taylor & Francis Journals, vol. 22(10), pages 796-800, July.
    See citations under working paper version above.
  32. Gresnigt, Francine & Kole, Erik & Franses, Philip Hans, 2015. "Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 123-139.
    See citations under working paper version above.
  33. Denice Bodeutsch & Philip Hans Franses, 2015. "The Stock Exchange of Suriname: Returns, Volatility, Correlations, and Weak-Form Efficiency," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(1), pages 130-139, January.
    See citations under working paper version above.
  34. Philip Franses & Rianne Legerstee, 2014. "Statistical institutes and economic prosperity," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 507-520, January.
    See citations under working paper version above.
  35. Mees, Heleen & Franses, Philip Hans, 2014. "Are individuals in China prone to money illusion?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 51(C), pages 38-46.

    Cited by:

    1. Lechthaler, Wolfgang & Mileva, Mariya, 2024. "Trade liberalization, wage inequality, and monetary policy," Journal of International Money and Finance, Elsevier, vol. 143(C).
    2. Elisa Darriet & Marianne Guille & Jean-Christophe Vergnaud & Mariko Shimizu, 2020. "Money illusion, financial literacy and numeracy: experimental evidence," Post-Print hal-02310038, HAL.
    3. Murota, Ryu-ichiro, 2019. "Negative interest rate policy in a permanent liquidity trap," MPRA Paper 93498, University Library of Munich, Germany.
    4. Thomas A. Stephens & Jean-Robert Tyran, 2016. "Money Illusion and Household Finance," Discussion Papers 16-14, University of Copenhagen. Department of Economics.
    5. Ryu‐ichiro Murota, 2018. "Aggregate demand deficiency, labor unions, and long‐run stagnation," Metroeconomica, Wiley Blackwell, vol. 69(4), pages 868-888, November.

  36. Rene Segers & Philip Hans Franses, 2014. "Panel design effects on response rates and response quality," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 1-24, February.
    See citations under working paper version above.
  37. Rianne Legerstee & Philip Hans Franses, 2014. "Do Experts’ SKU Forecasts Improve after Feedback?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 69-79, January.
    See citations under working paper version above.
  38. Dennis Fok & Richard Paap & Philip Hans Franses, 2014. "Incorporating Responsiveness to Marketing Efforts in Brand Choice Modeling," Econometrics, MDPI, vol. 2(1), pages 1-25, February.
    See citations under working paper version above.
  39. Denice Bodeutsch & Philip Hans Franses, 2014. "Size and value effects in Suriname," Applied Financial Economics, Taylor & Francis Journals, vol. 24(10), pages 671-677, May.
    See citations under working paper version above.
  40. Philip Hans Franses, 2014. "Trends in three decades of rankings of Dutch economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1257-1268, February.

    Cited by:

    1. Marcel Clermont & Alexander Dirksen & Barbara Scheidt & Dirk Tunger, 2017. "Citation metrics as an additional indicator for evaluating research performance? An analysis of their correlations and validity," Business Research, Springer;German Academic Association for Business Research, vol. 10(2), pages 249-279, October.
    2. Haucap, Justus & Muck, Johannes, 2013. "What drives the relevance and reputation of economics journals? An update from a survey among economists," DICE Discussion Papers 103, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    3. Wohlrabe, Klaus & Meyer, Justus, 2017. "Standing on the shoulder of giants: The aspect of free-riding in RePEc rankings," MPRA Paper 77782, University Library of Munich, Germany.
    4. Wohlrabe, Klaus & Friedrich, Elisabeth, 2016. "Ordinal ranking aggregation in bibliometric analysis," MPRA Paper 69144, University Library of Munich, Germany.
    5. Tom Coupé, 2021. "Who is the Most Sought-After Economist? Ranking Economists Using Google Trends," Working Papers in Economics 21/02, University of Canterbury, Department of Economics and Finance.
    6. Anne-Wil Harzing & Wilfred Mijnhardt, 2015. "Proof over promise: towards a more inclusive ranking of Dutch academics in Economics & Business," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 727-749, January.

  41. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    See citations under working paper version above.
  42. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.

    Cited by:

    1. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    2. Sroginis, Anna & Fildes, Robert & Kourentzes, Nikolaos, 2023. "Use of contextual and model-based information in adjusting promotional forecasts," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1177-1191.
    3. Michael McAleer & Felix Chan & Les Oxley, 2013. "Modelling and Simulation: An Overview," KIER Working Papers 865, Kyoto University, Institute of Economic Research.

  43. Philip Hans Franses & Heleen Mees, 2013. "Approximating the DGP of China's quarterly GDP," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3469-3472, August.
    See citations under working paper version above.
  44. Franses, Philip Hans & Legerstee, Rianne, 2013. "Do statistical forecasting models for SKU-level data benefit from including past expert knowledge?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 80-87.

    Cited by:

    1. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Baecke, Philippe & De Baets, Shari & Vanderheyden, Karlien, 2017. "Investigating the added value of integrating human judgement into statistical demand forecasting systems," International Journal of Production Economics, Elsevier, vol. 191(C), pages 85-96.
    4. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.
    5. Syntetos, Aris A. & Kholidasari, Inna & Naim, Mohamed M., 2016. "The effects of integrating management judgement into OUT levels: In or out of context?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 853-863.
    6. Fildes, Robert & Goodwin, Paul & Önkal, Dilek, 2019. "Use and misuse of information in supply chain forecasting of promotion effects," International Journal of Forecasting, Elsevier, vol. 35(1), pages 144-156.
    7. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    8. Alvarado-Valencia, Jorge & Barrero, Lope H. & Önkal, Dilek & Dennerlein, Jack T., 2017. "Expertise, credibility of system forecasts and integration methods in judgmental demand forecasting," International Journal of Forecasting, Elsevier, vol. 33(1), pages 298-313.
    9. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
    10. Maud van den Broeke & Shari de Baets & Ann Vereecke & Philippe Baecke & Karlien Vanderheyden, 2019. "Judgmental forecast adjustments over different time horizons," Post-Print hal-03001747, HAL.
    11. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.
    12. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.

  45. Chang, Chia-Lin & de Bruijn, Bert & Franses, Philip Hans & McAleer, Michael, 2013. "Analyzing fixed-event forecast revisions," International Journal of Forecasting, Elsevier, vol. 29(4), pages 622-627.
    See citations under working paper version above.
  46. Philip Hans Franses & Bert De Groot, 2013. "Do commercial real estate prices have predictive content for GDP?," Applied Economics, Taylor & Francis Journals, vol. 45(31), pages 4379-4384, November.
    See citations under working paper version above.
  47. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2013. "Are forecast updates progressive?," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 9-18.
    See citations under working paper version above.
  48. Franses, Philip Hans, 2013. "Data revisions and periodic properties of macroeconomic data," Economics Letters, Elsevier, vol. 120(2), pages 139-141.

    Cited by:

    1. Abo-Zaid, Salem, 2014. "Revisions to US labor market data and the public’s perception of the economy," Economics Letters, Elsevier, vol. 122(2), pages 119-124.
    2. Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 213.

  49. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
    See citations under working paper version above.
  50. Fok, Dennis & Paap, Richard & Franses, Philip Hans, 2012. "Modeling dynamic effects of promotion on interpurchase times," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3055-3069.
    See citations under working paper version above.
  51. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    See citations under working paper version above.
  52. de Groot, Bert & Franses, Philip Hans, 2012. "Common socio-economic cycle periods," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 59-68.

    Cited by:

    1. Schot, Johan & Kanger, Laur, 2018. "Deep transitions: Emergence, acceleration, stabilization and directionality," Research Policy, Elsevier, vol. 47(6), pages 1045-1059.
    2. de Groot, E.A. & Segers, R. & Prins, D., 2021. "Disentangling the enigma of multi-structured economic cycles - A new appearance of the golden ratio," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Grinin, Leonid E. & Grinin, Anton L. & Korotayev, Andrey, 2017. "Forthcoming Kondratieff wave, Cybernetic Revolution, and global ageing," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 52-68.
    4. Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2017. "Does technology cause business cycles in the USA? A Schumpeter-inspired approach," LSE Research Online Documents on Economics 80760, London School of Economics and Political Science, LSE Library.
    5. Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2017. "Technology and Business Cycles: A Schumpeterian Investigation for the USA," MPRA Paper 80636, University Library of Munich, Germany.
    6. de Bruijn, L.P. & Franses, Ph.H.B.F., 2015. "Stochastic levels and duration dependence in US unemployment," Econometric Institute Research Papers EI2015-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Inga Ivanova & Oivind Strand & Loet Leydesdorff, 2019. "The Synergy and Cycle Values in Regional Innovation Systems: The Case of Norway," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(1), pages 48-61.
    8. Alvarez-Ramirez, J. & Rodriguez, E. & Espinosa-Paredes, G., 2012. "A partisan effect in the efficiency of the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4923-4932.
    9. de Groot, E.A. & Segers, R. & Prins, D., 2022. "Non-resonating cycles in a dynamic model for investment behavior," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    10. Alvarez-Ramírez, José & Rodríguez, Eduardo, 2012. "Temporal variations of serial correlations of trading volume in the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4128-4135.

  53. Kiygi Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2012. "The effectiveness of high-frequency direct-response commercials," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 98-109.

    Cited by:

    1. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2021. "Forecasting time-varying arrivals: Impact of direct response advertising on call center performance," Journal of Business Research, Elsevier, vol. 131(C), pages 227-240.
    2. Kosse, Anneke, 2013. "Do newspaper articles on card fraud affect debit card usage?," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5382-5391.
    3. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2017. "Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 90-101.
    4. Eckert, C. & J. Hohberger (Jan) & Franses, Ph.H.B.F., 2022. "Gaussian Copula Regression in the Presence of Thresholds," Econometric Institute Research Papers 2022-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.

  54. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495, April.

    Cited by:

    1. Franses, Ph.H.B.F. & de Bruijn, L.P., 2015. "Benchmarking judgmentally adjusted forecasts," Econometric Institute Research Papers EI2015-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
    3. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    4. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    5. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    6. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
    7. Volha Audzei, 2016. "Confidence Cycles and Liquidity Hoarding," Working Papers 2016/07, Czech National Bank.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    9. Philip Hans Franses, 2024. "Incorporating judgment in forecasting models in times of crisis," Futures & Foresight Science, John Wiley & Sons, vol. 6(4), December.
    10. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
    11. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    12. Simionescu, Mihaela, 2014. "New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation || Nuevas estrategias para mejorar la exactitud," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 112-129, December.
    13. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    14. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    15. Philip Hans Franses & Max Welz, 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," JRFM, MDPI, vol. 13(3), pages 1-8, March.
    16. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.
    17. Simionescu, Mihaela, 2015. "A Comparative Analysis Of Macroeconomic Forecasts Accuracy In Spain And Romania," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 6(1), pages 67-74.
    18. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    19. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    20. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.

  55. Bram van Dijk & Philip Hans Franses & Richard Paap & Dick van Dijk, 2011. "Modelling regional house prices," Applied Economics, Taylor & Francis Journals, vol. 43(17), pages 2097-2110.
    See citations under working paper version above.
  56. P H Franses & R Legerstee, 2011. "Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 537-543, March.

    Cited by:

    1. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    4. Theocharis, Zoe & Harvey, Nigel, 2016. "Order effects in judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 32(1), pages 44-60.
    5. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    6. Maud van den Broeke & Shari de Baets & Ann Vereecke & Philippe Baecke & Karlien Vanderheyden, 2019. "Judgmental forecast adjustments over different time horizons," Post-Print hal-03001747, HAL.
    7. Larissa Koupriouchina & Jean-Pierre van der Rest & Zvi Schwartz, 2023. "Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts: Does User Override Frequency Impact Accuracy at Different Time Horizons?," Tourism Economics, , vol. 29(8), pages 2143-2164, December.
    8. Christiane B. Haubitz & Cedric A. Lehmann & Andreas Fügener & Ulrich W. Thonemann, 2021. "The Risk of Algorithm Transparency: How Algorithm Complexity Drives the Effects on Use of Advice," ECONtribute Discussion Papers Series 078, University of Bonn and University of Cologne, Germany.
    9. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.
    10. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.

  57. Philip Hans Franses & Richard Paap, 2011. "Random‐coefficient periodic autoregressions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(1), pages 101-115, February.
    See citations under working paper version above.
  58. Philip Hans Franses & Heleen Mees, 2011. "Does news on real Chinese GDP growth impact stock markets?," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 61-66.
    See citations under working paper version above.
  59. Robert M. Kunst & Philip Hans Franses, 2011. "Testing for Seasonal Unit Roots in Monthly Panels of Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(4), pages 469-488, August.
    See citations under working paper version above.
  60. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.

    Cited by:

    1. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    2. Antonis Michis, 2012. "Monitoring Forecasting Combinations with Semiparametric Regression Models," Working Papers 2012-2, Central Bank of Cyprus.
    3. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.

  61. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    See citations under working paper version above.
  62. Philip Hans Franses & Jeanine Kippers, 2010. "How do we pay with euro notes when some notes are missing? Empirical evidence from Monopoly® experiments," Applied Financial Economics, Taylor & Francis Journals, vol. 20(6), pages 459-464.

    Cited by:

    1. Philip Hans Franses & Max Welz, 2019. "Cash Use of the Taiwan Dollar: Is It Efficient? †," JRFM, MDPI, vol. 12(1), pages 1-6, January.

  63. Philip Hans Franses & J.S. Cramer, 2010. "On the number of categories in an ordered regression model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(1), pages 125-128, February.
    See citations under working paper version above.
  64. Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.

    Cited by:

    1. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    4. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    5. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
    7. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
    8. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2014. "The value of competitive information in forecasting FMCG retail product sales and the variable selection problem," European Journal of Operational Research, Elsevier, vol. 237(2), pages 738-748.
    9. Rianne Legerstee & Philip Hans Franses, 2011. "Do Experts' SKU Forecasts improve after Feedback?," Tinbergen Institute Discussion Papers 11-135/4, Tinbergen Institute.
    10. Trapero, Juan R. & Kourentzes, N. & Fildes, R., 2012. "Impact of information exchange on supplier forecasting performance," Omega, Elsevier, vol. 40(6), pages 738-747.
    11. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    12. Rianne Legerstee & Philip Hans Franses & Richard Paap, 2011. "Do Experts incorporate Statistical Model Forecasts and should they?," Tinbergen Institute Discussion Papers 11-141/4, Tinbergen Institute.
    13. Fildes, Robert & Goodwin, Paul & Önkal, Dilek, 2019. "Use and misuse of information in supply chain forecasting of promotion effects," International Journal of Forecasting, Elsevier, vol. 35(1), pages 144-156.
    14. Davydenko, Andrey & Fildes, Robert, 2013. "Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 510-522.
    15. Franses, Philip Hans & Legerstee, Rianne, 2013. "Do statistical forecasting models for SKU-level data benefit from including past expert knowledge?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 80-87.
    16. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    17. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    18. Khosrowabadi, Naghmeh & Hoberg, Kai & Imdahl, Christina, 2022. "Evaluating human behaviour in response to AI recommendations for judgemental forecasting," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1151-1167.
    19. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    20. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    21. Niematallah Elamin & Mototsugu Fukushige, 2017. "Integrating judgment in statistical demand forecasting: An approach to confront uncertainty," Discussion Papers in Economics and Business 17-20, Osaka University, Graduate School of Economics.
    22. Philip Hans Franses & Rianne Legerstee & Richard Paap, 2011. "Estimating Loss Functions of Experts," Tinbergen Institute Discussion Papers 11-177/4, Tinbergen Institute.
    23. Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023. "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 1-31, June.
    24. Goodwin, Paul & Sinan Gönül, M. & Önkal, Dilek, 2013. "Antecedents and effects of trust in forecasting advice," International Journal of Forecasting, Elsevier, vol. 29(2), pages 354-366.
    25. Boutselis, Petros & McNaught, Ken, 2019. "Using Bayesian Networks to forecast spares demand from equipment failures in a changing service logistics context," International Journal of Production Economics, Elsevier, vol. 209(C), pages 325-333.
    26. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.
    27. Katsagounos, Ilias & Thomakos, Dimitrios D. & Litsiou, Konstantia & Nikolopoulos, Konstantinos, 2021. "Superforecasting reality check: Evidence from a small pool of experts and expedited identification," European Journal of Operational Research, Elsevier, vol. 289(1), pages 107-117.
    28. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.
    29. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    30. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.
    31. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.

  65. Boswijk, H. Peter & Franses, Philip Hans & van Dijk, Dick, 2010. "Cointegration in a historical perspective," Journal of Econometrics, Elsevier, vol. 158(1), pages 156-159, September.
    See citations under working paper version above.
  66. Philip Hans Franses & Rianne Legerstee, 2010. "A Unifying View On Multi‐Step Forecasting Using An Autoregression," Journal of Economic Surveys, Wiley Blackwell, vol. 24(3), pages 389-401, July.

    Cited by:

    1. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

  67. Sabine Knapp & Philip Hans Franses, 2009. "Comprehensive Review of the Maritime Safety Regimes: Present Status and Recommendations for Improvements," Transport Reviews, Taylor & Francis Journals, vol. 30(2), pages 241-270, April.

    Cited by:

    1. Knapp, S. & Bijwaard, G.E. & Heij, C., 2010. "Estimated Incident Cost Savings in Shipping Due to Inspections," Econometric Institute Research Papers EI 2010-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  68. Zsolt Sándor & Philip Hans Franses, 2009. "Consumer price evaluations through choice experiments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 517-535, April.

    Cited by:

    1. Nicoletti, Cheti & Auspurg, Katrin & Iacovou, Maria, 2015. "Housework share between partners: experimental evidence on gender identity," ISER Working Paper Series 2015-03, Institute for Social and Economic Research.
    2. Assele, Samson Yaekob & Meulders, Michel & Vandebroek, Martina, 2023. "Sample size selection for discrete choice experiments using design features," Journal of choice modelling, Elsevier, vol. 49(C).
    3. Vishva Danthurebandara & Jie Yu & Martina Vandebroek, 2015. "Designing choice experiments by optimizing the complexity level to individual abilities," Quantitative Marketing and Economics (QME), Springer, vol. 13(1), pages 1-26, March.
    4. Fiebig, D.G. & Viney, R. & Haas, M. & Knox, S. & Street, D. & Weisberg, E. & Bateson, D., 2015. "Complexity and doctor choices when discussing contraceptives," Health, Econometrics and Data Group (HEDG) Working Papers 15/14, HEDG, c/o Department of Economics, University of York.

  69. Philip Hans Franses & Bert de Groot & Rianne Legerstee, 2009. "Testing for harmonic regressors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(3), pages 339-346.
    See citations under working paper version above.
  70. Philip Hans Franses, 2009. "Why is GDP typically revised upwards?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 125-130, May.

    Cited by:

    1. Franses, Philip Hans, 2013. "Data revisions and periodic properties of macroeconomic data," Economics Letters, Elsevier, vol. 120(2), pages 139-141.
    2. Semieniuk, Gregor, 2024. "Inconsistent definitions of GDP: Implications for estimates of decoupling," Ecological Economics, Elsevier, vol. 215(C).
    3. Henk Kranendonk & Johan Verbruggen, 2009. "Reaction to Philip Hans Franses’ Note ‘Why is GDP typically revised upwards?’," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 133-134, May.

  71. Prins, Remco & Verhoef, Peter C. & Franses, Philip Hans, 2009. "The impact of adoption timing on new service usage and early disadoption," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 304-313.

    Cited by:

    1. Madhavan Parthasarathy & Walfried Lassar, 2023. "The adoption and disadoption of electric vehicles by innovators," Marketing Letters, Springer, vol. 34(4), pages 549-573, December.
    2. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Predicting diffusion dynamics and launch time strategy for mobile telecommunication services: an empirical analysis," Information Technology and Management, Springer, vol. 22(1), pages 33-51, March.
    3. Healey, John & Moe, Wendy W., 2016. "The effects of installed base innovativeness and recency on content sales in a platform-mediated market," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 246-260.
    4. Ruiz-Mercado, Ilse & Masera, Omar & Zamora, Hilda & Smith, Kirk R., 2011. "Adoption and sustained use of improved cookstoves," Energy Policy, Elsevier, vol. 39(12), pages 7557-7566.
    5. Thomas Chesney & Shaun Lawson, 2015. "Critical Mass and Discontinued Use of Social Media," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(3), pages 376-387, May.
    6. Hoffmann, Arvid O.I. & Broekhuizen, Thijs L.J., 2010. "Understanding investors' decisions to purchase innovative products: Drivers of adoption timing and range," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 342-355.
    7. Ashish Sood & V Kumar, 2018. "Client profitability of diffusion segments across countries for multi-generational innovations: The influence of firm, market, and cross-national differences," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 49(9), pages 1237-1262, December.
    8. Konya-Baumbach, Elisa & Schuhmacher, Monika C. & Kuester, Sabine & Kuharev, Victoria, 2019. "Making a first impression as a start-up: Strategies to overcome low initial trust perceptions in digital innovation adoption," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 385-399.
    9. Landsman, Vardit & Nitzan, Irit, 2020. "Cross-decision social effects in product adoption and defection decisions," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 213-235.
    10. Muller, Eitan, 2020. "Delimiting disruption: Why Uber is disruptive, but Airbnb is not," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 43-55.
    11. Miremadi, Iman & Khoshbash, Mostafa & Saeedian, MohammadMahdi, 2023. "Fostering generativity in platform ecosystems: How open innovation and complexity interact to influence platform adoption," Research Policy, Elsevier, vol. 52(6).
    12. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    13. Donald R. Lehmann & Jeffrey R. Parker, 2017. "Disadoption," AMS Review, Springer;Academy of Marketing Science, vol. 7(1), pages 36-51, June.
    14. Christophe Van den Bulte & Raghuram Iyengar, 2011. "Tricked by Truncation: Spurious Duration Dependence and Social Contagion in Hazard Models," Marketing Science, INFORMS, vol. 30(2), pages 233-248, 03-04.
    15. Liu, Huan & Sese, F. Javier, 2022. "The Impact of Mobile App Adoption on Cross-buying: The Moderating Roles of Product Category Characteristics and Adoption Timing," Journal of Retailing, Elsevier, vol. 98(2), pages 241-259.
    16. Moldovan, Sarit & Muller, Eitan & Richter, Yossi & Yom-Tov, Elad, 2017. "Opinion leadership in small groups," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 536-552.

  72. Bijwaard, Govert E. & Franses, Philip Hans, 2009. "The effect of rounding on payment efficiency," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1449-1461, February.

    Cited by:

    1. Arkadiusz Manikowski, 2017. "Analysis of the denomination structure of the Polish currency in the context of the launch of the new 500 zloty banknote," Bank i Kredyt, Narodowy Bank Polski, vol. 48(5), pages 495-530.

  73. Youssef Boulaksil & Philip Hans Franses, 2009. "Experts' Stated Behavior," Interfaces, INFORMS, vol. 39(2), pages 168-171, April.
    • Boulaksil, Y. & Franses, Ph.H.B.F., 2008. "Experts' Stated Behavior," ERIM Report Series Research in Management ERS-2008-001-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    See citations under working paper version above.
  74. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346, August.
    See citations under working paper version above.
  75. van Diepen, Merel & Donkers, Bas & Franses, Philip Hans, 2009. "Does irritation induced by charitable direct mailings reduce donations?," International Journal of Research in Marketing, Elsevier, vol. 26(3), pages 180-188.
    See citations under working paper version above.
  76. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.

    Cited by:

    1. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    3. Irfan Akbar Kazi & Suzanne Salloy, 2014. "Dynamics in the correlations of the Credit Default Swaps’ G14 dealers: Are there any contagion effects due to Lehman Brothers’ bankruptcy and the global financial crisis?," Working Papers 2014-237, Department of Research, Ipag Business School.
    4. Caporin, M. & McAleer, M.J., 2013. "Ten Things You Should Know About DCC," Econometric Institute Research Papers EI 2013-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    6. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    7. Gian Piero Aielli & Massimiliano Caporin, 2011. "Variance Clustering Improved Dynamic Conditional Correlation MGARCH Estimators," "Marco Fanno" Working Papers 0133, Dipartimento di Scienze Economiche "Marco Fanno".
    8. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," KIER Working Papers 870, Kyoto University, Institute of Economic Research.
    9. Audrone Virbickaite & M. Concepci'on Aus'in & Pedro Galeano, 2013. "A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model With Application to Portfolio Selection," Papers 1301.5129, arXiv.org, revised Jan 2014.
    10. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    11. Panagiotis G. Papaioannou & George P. Papaioannou & Kostas Siettos & Akylas Stratigakos & Christos Dikaiakos, 2017. "Dynamic Conditional Correlation between Electricity and Stock markets during the Financial Crisis in Greece," Papers 1708.07063, arXiv.org.
    12. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    13. Mahan Tahvildari, 2021. "Forward indifference valuation and hedging of basis risk under partial information," Papers 2101.00251, arXiv.org.
    14. Mehmet Sahiner, 2024. "Volatility Spillovers and Contagion During Major Crises: An Early Warning Approach Based on a Deep Learning Model," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2435-2499, June.
    15. Caporin, M. & McAleer, M.J., 2010. "Ranking multivariate GARCH models by problem dimension," Econometric Institute Research Papers EI 2010-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Fresoli, Diego E. & Ruiz, Esther, 2016. "The uncertainty of conditional returns, volatilities and correlations in DCC models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 170-185.
    17. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    18. Hafner, C. & Reznikova, O., 2010. "On the estimation of dynamic conditional correlation models," LIDAM Discussion Papers ISBA 2010006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    20. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH models," Economics Series Working Papers 594, University of Oxford, Department of Economics.
    21. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    22. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.
    24. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    25. Dick van Dijk & Haris Munandar & Christian Hafner, 2011. "The euro introduction and noneuro currencies," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 95-116.
    26. Irfan Akbar Kazi & Suzanne Salloy, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis - From the perspective of the Credit Default Swaps’ G14 dealers," Working Papers hal-04141216, HAL.
    27. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.
    28. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    29. Tetsuji Tanaka & Jin Guo, 2020. "How does the self-sufficiency rate affect international price volatility transmissions in the wheat sector? Evidence from wheat-exporting countries," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    30. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    31. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
    32. Carnero M. Angeles & Eratalay M. Hakan, 2014. "Estimating VAR-MGARCH models in multiple steps," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 339-365, May.
    33. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    34. Irfan Akbar Kazi & Suzanne Salloy, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis - From the perspective of the Credit Default Swaps’ G14 dealers," EconomiX Working Papers 2013-6, University of Paris Nanterre, EconomiX.
    35. BAUWENS, Luc & GRIGORYEVA, Lyudmila & ORTEGA, Juan-Pablo, 2014. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," LIDAM Discussion Papers CORE 2014012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    36. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "An Alternative Approach to Measure Co-Movement between Two Time Series," Mathematics, MDPI, vol. 8(2), pages 1-24, February.
    37. Suzanne Salloy & Irfan Akbar Kazi, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis: From the perspective of the Credit Default Swaps’ G14 dealers," Erudite Working Paper 2013-02, Erudite.
    38. S.T. Boris Choy & Cathy W.S. Chen & Edward M.H. Lin, 2014. "Bivariate asymmetric GARCH models with heavy tails and dynamic conditional correlations," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1297-1313, July.
    39. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    40. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    41. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
    42. Saranya, K. & Prasanna, P. Krishna, 2018. "Estimating stochastic volatility with jumps and asymmetry in Asian markets," Finance Research Letters, Elsevier, vol. 25(C), pages 145-153.
    43. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.

  77. Franses, Philip Hans & Legerstee, Rianne, 2009. "Properties of expert adjustments on model-based SKU-level forecasts," International Journal of Forecasting, Elsevier, vol. 25(1), pages 35-47.

    Cited by:

    1. De Baets, Shari & Harvey, Nigel, 2018. "Forecasting from time series subject to sporadic perturbations: Effectiveness of different types of forecasting support," International Journal of Forecasting, Elsevier, vol. 34(2), pages 163-180.
    2. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    4. Sroginis, Anna & Fildes, Robert & Kourentzes, Nikolaos, 2023. "Use of contextual and model-based information in adjusting promotional forecasts," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1177-1191.
    5. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    6. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Danese, Pamela & Kalchschmidt, Matteo, 2011. "The role of the forecasting process in improving forecast accuracy and operational performance," International Journal of Production Economics, Elsevier, vol. 131(1), pages 204-214, May.
    8. Baecke, Philippe & De Baets, Shari & Vanderheyden, Karlien, 2017. "Investigating the added value of integrating human judgement into statistical demand forecasting systems," International Journal of Production Economics, Elsevier, vol. 191(C), pages 85-96.
    9. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    10. Trapero, Juan R. & Pedregal, Diego J. & Fildes, R. & Kourentzes, N., 2013. "Analysis of judgmental adjustments in the presence of promotions," International Journal of Forecasting, Elsevier, vol. 29(2), pages 234-243.
    11. Rianne Legerstee & Philip Hans Franses, 2011. "Do Experts' SKU Forecasts improve after Feedback?," Tinbergen Institute Discussion Papers 11-135/4, Tinbergen Institute.
    12. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.
    13. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    14. Syntetos, Aris A. & Kholidasari, Inna & Naim, Mohamed M., 2016. "The effects of integrating management judgement into OUT levels: In or out of context?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 853-863.
    15. Rianne Legerstee & Philip Hans Franses & Richard Paap, 2011. "Do Experts incorporate Statistical Model Forecasts and should they?," Tinbergen Institute Discussion Papers 11-141/4, Tinbergen Institute.
    16. Franses, Philip Hans & Legerstee, Rianne, 2013. "Do statistical forecasting models for SKU-level data benefit from including past expert knowledge?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 80-87.
    17. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    18. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    19. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    20. Khosrowabadi, Naghmeh & Hoberg, Kai & Imdahl, Christina, 2022. "Evaluating human behaviour in response to AI recommendations for judgemental forecasting," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1151-1167.
    21. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    22. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    23. P H Franses & R Legerstee, 2011. "Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 537-543, March.
    24. Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.
    25. Maud van den Broeke & Shari de Baets & Ann Vereecke & Philippe Baecke & Karlien Vanderheyden, 2019. "Judgmental forecast adjustments over different time horizons," Post-Print hal-03001747, HAL.
    26. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.
    27. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.
    28. A A Syntetos & N C Georgantzas & J E Boylan & B C Dangerfield, 2011. "Judgement and supply chain dynamics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1138-1158, June.
    29. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.
    30. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.
    31. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2009. "How Accurate are Government Forecast of Economic Fundamentals?," Econometric Institute Research Papers EI 2009-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  78. Philip Hans Franses, 2009. "Can Managers Judgmental Forecasts Be Made Scientifically?," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 15, pages 32-36, Fall.

    Cited by:

    1. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.

  79. Knapp, Sabine & Franses, Philip Hans, 2009. "Does ratification matter and do major conventions improve safety and decrease pollution in shipping?," Marine Policy, Elsevier, vol. 33(5), pages 826-846, September.
    See citations under working paper version above.
  80. Erjen van Nierop & Dennis Fok & Philip Hans Franses, 2008. "Interaction Between Shelf Layout and Marketing Effectiveness and Its Impact on Optimizing Shelf Arrangements," Marketing Science, INFORMS, vol. 27(6), pages 1065-1082, 11-12.
    See citations under working paper version above.
  81. Knapp, Sabine & Franses, Philip Hans, 2008. "Econometric analysis to differentiate effects of various ship safety inspections," Marine Policy, Elsevier, vol. 32(4), pages 653-662, July.

    Cited by:

    1. Heij, C. & Bijwaard, G.E. & Knapp, S., 2010. "Ship Inspection Strategies: Effects on Maritime Safety and Environmental Protection," Econometric Institute Research Papers EI 2010-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. François Fulconis & Raphael Lissillour, 2021. "Toward a behavioral approach of international shipping: a study of the inter-organisational dynamics of maritime safety," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-23, December.
    3. Knapp, S. & Heij, C., 2019. "Improved strategies for the maritime industry to target vessels for inspection and to select inspection priority areas," Econometric Institute Research Papers EI2019-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Esma Gül Emecen Kara, 2016. "Risk Assessment in the Istanbul Strait Using Black Sea MOU Port State Control Inspections," Sustainability, MDPI, vol. 8(4), pages 1-17, April.
    5. Yan, Ran & Mo, Haoyu & Guo, Xiaomeng & Yang, Ying & Wang, Shuaian, 2022. "Is port state control influenced by the COVID-19? Evidence from inspection data," Transport Policy, Elsevier, vol. 123(C), pages 82-103.
    6. Fan, Lixian & Luo, Meifeng & Yin, Jinbo, 2014. "Flag choice and Port State Control inspections—Empirical evidence using a simultaneous model," Transport Policy, Elsevier, vol. 35(C), pages 350-357.
    7. Graziano, Armando & Mejia, Maximo Q. & Schröder-Hinrichs, Jens-Uwe, 2018. "Achievements and challenges on the implementation of the European Directive on Port State Control," Transport Policy, Elsevier, vol. 72(C), pages 97-108.
    8. Cariou, Pierre & Wolff, Francois-Charles, 2015. "Identifying substandard vessels through Port State Control inspections: A new methodology for Concentrated Inspection Campaigns," Marine Policy, Elsevier, vol. 60(C), pages 27-39.

  82. Philip Hans Franses & Marco van der Leij & Richard Paap, 2008. "A Simple Test for GARCH Against a Stochastic Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 291-306, Summer.

    Cited by:

    1. Dongming Zhu & John W. Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
    2. Mustafa Caglayan & Ozge Kandemir Kocaaslan & Kostas Mouratidis, 2016. "Regime Dependent Effects of Inflation Uncertainty on Real Growth: A Markov Switching Approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(2), pages 135-155, May.
    3. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. M. Berument & Yeliz Yalcin & Julide Yildirim, 2011. "The inflation and inflation uncertainty relationship for Turkey: a dynamic framework," Empirical Economics, Springer, vol. 41(2), pages 293-309, October.
    5. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2011. "Real effects of inflation uncertainty in the US," Working Papers 2011002, The University of Sheffield, Department of Economics, revised Feb 2015.
    6. Veronika Czellar & David T. Frazier & Eric Renault, 2020. "Approximate Maximum Likelihood for Complex Structural Models," Papers 2006.10245, arXiv.org.
    7. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2021. "Approximate Maximum Likelihood for Complex Structural Models," The Warwick Economics Research Paper Series (TWERPS) 1337, University of Warwick, Department of Economics.

  83. Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.

    Cited by:

    1. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    3. Claudio Felisoni de Angelo & Ronaldo Zwicker & Nuno Manoel Martins Dias Fouto & Marcos Roberto Luppe, 2011. "Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast," Brazilian Business Review, Fucape Business School, vol. 8(2), pages 01-21, April.
    4. Marcel Boumans, 2016. "Methodological institutionalism as a transformation of structural econometrics," Review of Political Economy, Taylor & Francis Journals, vol. 28(3), pages 417-425, July.
    5. Boulaksil, Y. & Franses, Ph.H.B.F., 2008. "Experts' Stated Behavior," ERIM Report Series Research in Management ERS-2008-001-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    7. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
    8. Fenfen Wei & Nanping Feng & Kevin H. Zhang, 2017. "Innovation Capability and Innovation Talents: Evidence from China Based on a Quantile Regression Approach," Sustainability, MDPI, vol. 9(7), pages 1-15, July.
    9. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2009. "How Accurate are Government Forecast of Economic Fundamentals?," Econometric Institute Research Papers EI 2009-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  84. Franses, Philip Hans & van Oest, Rutger, 2007. "On the econometrics of the geometric lag model," Economics Letters, Elsevier, vol. 95(2), pages 291-296, May.

    Cited by:

    1. Marcus Scheiblecker, 2017. "Modelling Short-run Money Demand for the US," Applied Economics and Finance, Redfame publishing, vol. 4(5), pages 9-20, September.
    2. Jifeng Mu & Jonathan Zhang & Abhishek Borah & Jiayin Qi, 2022. "Creative Appeals in Firm-Generated Content and Product Performance," Information Systems Research, INFORMS, vol. 33(1), pages 18-42, March.
    3. Feeny, Simon & Fry, Tim R.L., 2014. "How sustainable is the macroeconomic impact of foreign aid?," Journal of Policy Modeling, Elsevier, vol. 36(6), pages 1066-1081.
    4. Marcus Scheiblecker, 2012. "Between Cointegration and Multicointegration. Modelling Time Series Dynamics by Cumulative Error Correction Models," WIFO Working Papers 431, WIFO.
    5. Achintya Ray & Malcom Getz, 2018. "Excess Capacity and the Economics of Public Transit Investment: A Study of a Growing American City," Accounting and Finance Research, Sciedu Press, vol. 7(3), pages 119-119, August.
    6. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.

  85. Fok, Dennis & Franses, Philip Hans, 2007. "Modeling the diffusion of scientific publications," Journal of Econometrics, Elsevier, vol. 139(2), pages 376-390, August.
    See citations under working paper version above.
  86. Knapp, Sabine & Franses, Philip Hans, 2007. "Econometric analysis on the effect of port state control inspections on the probability of casualty: Can targeting of substandard ships for inspections be improved?," Marine Policy, Elsevier, vol. 31(4), pages 550-563, July.

    Cited by:

    1. Xiao, Yi & Wang, Grace & Ge, Ying-En & Xu, Qinyi & Li, Kevin X., 2021. "Game model for a new inspection regime of port state control under different reward and punishment conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    2. Jose Manuel Prieto & Victor Amor & Ignacio Turias & David Almorza & Francisco Piniella, 2021. "Evaluation of Paris MoU Maritime Inspections Using a STATIS Approach," Mathematics, MDPI, vol. 9(17), pages 1-13, August.
    3. Yang, Zhisen & Wan, Chengpeng & Yu, Qing & Yin, Jingbo & Yang, Zaili, 2023. "A machine learning-based Bayesian model for predicting the duration of ship detention in PSC inspection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    4. Wang, Yuhong & Zhang, Fan & Yang, Zhisen & Yang, Zaili, 2021. "Incorporation of deficiency data into the analysis of the dependency and interdependency among the risk factors influencing port state control inspection," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    5. Heij, C. & Bijwaard, G.E. & Knapp, S., 2010. "Ship Inspection Strategies: Effects on Maritime Safety and Environmental Protection," Econometric Institute Research Papers EI 2010-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Wang, Shuaian & Yan, Ran & Qu, Xiaobo, 2019. "Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 129-157.
    7. Jose Manuel Prieto & Víctor Amor-Esteban & David Almorza-Gomar & Ignacio Turias & Francisco Piniella, 2023. "Application of Multivariate Statistical Techniques as an Indicator of Variability of the Effects of COVID-19 on the Paris Memorandum of Understanding on Port State Control," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    8. Knapp, S. & Bijwaard, G.E. & Heij, C., 2010. "Estimated Incident Cost Savings in Shipping Due to Inspections," Econometric Institute Research Papers EI 2010-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Esma Gül Emecen Kara, 2016. "Risk Assessment in the Istanbul Strait Using Black Sea MOU Port State Control Inspections," Sustainability, MDPI, vol. 8(4), pages 1-17, April.
    10. Fan, Lixian & Luo, Meifeng & Yin, Jinbo, 2014. "Flag choice and Port State Control inspections—Empirical evidence using a simultaneous model," Transport Policy, Elsevier, vol. 35(C), pages 350-357.
    11. Yang, Zhisen & Yu, Qing & Yang, Zaili & Wan, Chengpeng, 2024. "A data-driven Bayesian model for evaluating the duration of detention of ships in PSC inspections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    12. Xiao, Yi & Qi, Guanqiu & Jin, Mengjie & Yuen, Kum Fai & Chen, Zhuo & Li, Kevin X., 2021. "Efficiency of Port State Control inspection regimes: A comparative study," Transport Policy, Elsevier, vol. 106(C), pages 165-172.
    13. Yang, Zhisen & Yang, Zaili & Teixeira, Angelo Palos, 2020. "Comparative analysis of the impact of new inspection regime on port state control inspection," Transport Policy, Elsevier, vol. 92(C), pages 65-80.
    14. Yang, Zhisen & Yang, Zaili & Yin, Jingbo & Qu, Zhuohua, 2018. "A risk-based game model for rational inspections in port state control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 477-495.
    15. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.

  87. van Dijk, Dick & Hans Franses, Philip & Peter Boswijk, H., 2007. "Absorption of shocks in nonlinear autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4206-4226, May.

    Cited by:

    1. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    2. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
    3. Dong, Minyi & Chang, Chun-Ping & Gong, Qiang & Chu, Yin, 2019. "Revisiting global economic activity and crude oil prices: A wavelet analysis," Economic Modelling, Elsevier, vol. 78(C), pages 134-149.
    4. Woo, Kai-Yin & Lee, Shu-Kam & Chan, Alan, 2014. "Non-linear adjustments to intranational PPP," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 360-371.
    5. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Strohsal, Till & Winkelmann, Lars, 2012. "Assessing the anchoring of inflation expectations," SFB 649 Discussion Papers 2012-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Zhang, Wenbei & Luckert, Marty & Qiu, Feng, 2023. "Asymmetric price transmission and impulse responses from U.S. crude oil to jet fuel and diesel markets," Energy, Elsevier, vol. 283(C).
    8. Pavlidis, Efthymios G. & Paya, Ivan & Peel, David A., 2011. "Real exchange rates and time-varying trade costs," Journal of International Money and Finance, Elsevier, vol. 30(6), pages 1157-1179, October.
    9. Pragidis, I.C. & Tsintzos, P. & Plakandaras, B., 2018. "Asymmetric effects of government spending shocks during the financial cycle," Economic Modelling, Elsevier, vol. 68(C), pages 372-387.
    10. Franchi, Massimo & Ordóñez, Javier, 2011. "Multiple equilibria in Spanish unemployment," Structural Change and Economic Dynamics, Elsevier, vol. 22(1), pages 71-80, February.
    11. Fanelli, Luca & Paruolo, Paolo, 2007. "Speed of Adjustment in Cointegrated Systems," MPRA Paper 9174, University Library of Munich, Germany.
    12. M. Berument & Yeliz Yalcin & Julide Yildirim, 2011. "The inflation and inflation uncertainty relationship for Turkey: a dynamic framework," Empirical Economics, Springer, vol. 41(2), pages 293-309, October.
    13. Ivan Paya & David A. Peel, 2011. "Systematic sampling of nonlinear models: Evidence on speed of adjustment in index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 192-203, February.
    14. Rahman, Sajjadur & Serletis, Apostolos, 2010. "The asymmetric effects of oil price and monetary policy shocks: A nonlinear VAR approach," Energy Economics, Elsevier, vol. 32(6), pages 1460-1466, November.
    15. Efthymios Pavlidis & Ivan Paya & David Peel, 2010. "Further empirical evidence on the consumption-real exchange rate anomaly," Working Papers 447022, Lancaster University Management School, Economics Department.
    16. Efthymios Pavlidis & Nicos Pavlidis, 2012. "Dynamic Estimation of Trade Costs from Real Exchange Rates," Working Papers 21883757, Lancaster University Management School, Economics Department.
    17. Strohsal, Till & Winkelmann, Lars, 2015. "Assessing the anchoring of inflation expectations," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 33-48.
    18. Frédéric Karamé, 2015. "Asymmetries and Markov-switching structural VAR," Post-Print hal-02296101, HAL.
    19. Lo Ming Chien, 2008. "Nonlinear PPP Deviations: A Monte Carlo Investigation of Their Unconditional Half-Life," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-31, December.

  88. Franses, Philip Hans & Kippers, Jeanine, 2007. "An empirical analysis of euro cash payments," European Economic Review, Elsevier, vol. 51(8), pages 1985-1997, November.
    See citations under working paper version above.
  89. Sabine Knapp & Philip Hans Franses, 2007. "A global view on port state control: econometric analysis of the differences across port state control regimes," Maritime Policy & Management, Taylor & Francis Journals, vol. 34(5), pages 453-482, October.

    Cited by:

    1. Xiao, Yi & Wang, Grace & Ge, Ying-En & Xu, Qinyi & Li, Kevin X., 2021. "Game model for a new inspection regime of port state control under different reward and punishment conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    2. Jose Manuel Prieto & Victor Amor & Ignacio Turias & David Almorza & Francisco Piniella, 2021. "Evaluation of Paris MoU Maritime Inspections Using a STATIS Approach," Mathematics, MDPI, vol. 9(17), pages 1-13, August.
    3. Helena Ukić Boljat & Merica Slišković & Igor Jelaska & Anita Gudelj & Gorana Jelić Mrčelić, 2020. "Analysis of Pollution Related Deficiencies Identified through PSC Inspections for the Period 2014–2018," Sustainability, MDPI, vol. 12(15), pages 1-13, July.
    4. Wang, Yuhong & Zhang, Fan & Yang, Zhisen & Yang, Zaili, 2021. "Incorporation of deficiency data into the analysis of the dependency and interdependency among the risk factors influencing port state control inspection," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    5. Heij, C. & Bijwaard, G.E. & Knapp, S., 2010. "Ship Inspection Strategies: Effects on Maritime Safety and Environmental Protection," Econometric Institute Research Papers EI 2010-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Wang, Shuaian & Yan, Ran & Qu, Xiaobo, 2019. "Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 129-157.
    7. Heij, C. & Knapp, S., 2018. "Predictive power of inspection outcomes for future shipping accidents," Econometric Institute Research Papers EI2018-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Emre Akyuz & Hristos Karahalios & Metin Celik, 2015. "Assessment of the maritime labour convention compliance using balanced scorecard and analytic hierarchy process approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(2), pages 145-162, February.
    9. Ji, X. & Brinkhuis, J. & Knapp, S., 2014. "A method to measure enforcement effort in shipping with incomplete information," Econometric Institute Research Papers EI 2014-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Knapp, S. & van de Velden, M., 2021. "Exploration of machine learning algorithms for maritime risk applications," Econometric Institute Research Papers 2021-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Jose Manuel Prieto & Víctor Amor-Esteban & David Almorza-Gomar & Ignacio Turias & Francisco Piniella, 2023. "Application of Multivariate Statistical Techniques as an Indicator of Variability of the Effects of COVID-19 on the Paris Memorandum of Understanding on Port State Control," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    12. Knapp, S. & Bijwaard, G.E. & Heij, C., 2010. "Estimated Incident Cost Savings in Shipping Due to Inspections," Econometric Institute Research Papers EI 2010-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Heij, C. & Knapp, S., 2011. "Risk evaluation methods at individual ship and company level," Econometric Institute Research Papers EI2011-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Ji, Xichen & Brinkhuis, Jan & Knapp, Sabine, 2015. "A method to measure enforcement effort in shipping with incomplete information," Marine Policy, Elsevier, vol. 60(C), pages 162-170.
    15. Meifeng Luo & Sung-Ho Shin & Young-Tae Chang, 2017. "Duration analysis for recurrent ship accidents," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(5), pages 603-622, July.
    16. Esma Gül Emecen Kara, 2016. "Risk Assessment in the Istanbul Strait Using Black Sea MOU Port State Control Inspections," Sustainability, MDPI, vol. 8(4), pages 1-17, April.
    17. Liangxia Zhong & Jiaxin Wu & Yiqing Wen & Bingjie Yang & Manel Grifoll & Yunping Hu & Pengjun Zheng, 2023. "Analysis of Factors Affecting the Effectiveness of Oil Spill Clean-Up: A Bayesian Network Approach," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    18. Antão, P. & Sun, S. & Teixeira, A.P. & Guedes Soares, C., 2023. "Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    19. Heij, C. & Knapp, S., 2018. "Shipping Inspections, Detentions, and Accidents: An Empirical Analysis of Risk Dimensions," Econometric Institute Research Papers 2018-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Yan, Ran & Wang, Shuaian & Fagerholt, Kjetil, 2020. "A semi-“smart predict then optimize” (semi-SPO) method for efficient ship inspection," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 100-125.
    21. Yan, Ran & Mo, Haoyu & Guo, Xiaomeng & Yang, Ying & Wang, Shuaian, 2022. "Is port state control influenced by the COVID-19? Evidence from inspection data," Transport Policy, Elsevier, vol. 123(C), pages 82-103.
    22. Monios, Jason & Wilmsmeier, Gordon & Tello, Gustavo Andrés Martínez & Pomaska, Lara, 2024. "A new conception of port governance under climate change," Journal of Transport Geography, Elsevier, vol. 120(C).
    23. Fan, Lixian & Luo, Meifeng & Yin, Jinbo, 2014. "Flag choice and Port State Control inspections—Empirical evidence using a simultaneous model," Transport Policy, Elsevier, vol. 35(C), pages 350-357.
    24. Knapp, S. & van de Velden, M., 2010. "Visualization of Ship Risk Profiles for the Shipping Industry," ERIM Report Series Research in Management ERS-2010-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    25. Yang, Zaili & Ng, Adolf K.Y. & Wang, Jin, 2014. "A new risk quantification approach in port facility security assessment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 72-90.
    26. Perepelkin, M. & Knapp, S. & Perepelkin, G. & de Pooter, M.D., 2009. "A method to measure flag performance for the shipping industry," Econometric Institute Research Papers EI 2009-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    27. Xiao, Yi & Qi, Guanqiu & Jin, Mengjie & Yuen, Kum Fai & Chen, Zhuo & Li, Kevin X., 2021. "Efficiency of Port State Control inspection regimes: A comparative study," Transport Policy, Elsevier, vol. 106(C), pages 165-172.
    28. Yang, Zhisen & Yang, Zaili & Teixeira, Angelo Palos, 2020. "Comparative analysis of the impact of new inspection regime on port state control inspection," Transport Policy, Elsevier, vol. 92(C), pages 65-80.
    29. Graziano, Armando & Mejia, Maximo Q. & Schröder-Hinrichs, Jens-Uwe, 2018. "Achievements and challenges on the implementation of the European Directive on Port State Control," Transport Policy, Elsevier, vol. 72(C), pages 97-108.
    30. Yang, Zhisen & Yang, Zaili & Yin, Jingbo & Qu, Zhuohua, 2018. "A risk-based game model for rational inspections in port state control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 477-495.
    31. Cariou, Pierre & Wolff, Francois-Charles, 2015. "Identifying substandard vessels through Port State Control inspections: A new methodology for Concentrated Inspection Campaigns," Marine Policy, Elsevier, vol. 60(C), pages 27-39.
    32. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    33. Heij, C. & Knapp, S., 2014. "Effects of wind strength and wave height on ship incident risk: regional trends and seasonality," Econometric Institute Research Papers EI2014-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    34. Armando Graziano & Pierre Cariou & François-Charles Wolff & Maximo Mejia & Jens-Uwe Schröder-Hinrichs, 2017. "Port state control inspections in the European Union: Do inspector's number and background matter?," Working Papers halshs-01649418, HAL.

  90. Philip Hans Franses, 2007. "Constant vs. Changing Seasonality," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 6, pages 24-25, Spring.

    Cited by:

    1. Capistrán Carlos & Constandse Christian & Ramos Francia Manuel, 2009. "Using Seasonal Models to Forecast Short-Run Inflation in Mexico," Working Papers 2009-05, Banco de México.
    2. Capistrán, Carlos & Constandse, Christian & Ramos-Francia, Manuel, 2010. "Multi-horizon inflation forecasts using disaggregated data," Economic Modelling, Elsevier, vol. 27(3), pages 666-677, May.

  91. Philip Hans Franses, 2007. "Estimating the stock of postwar Dutch postal stamps," Applied Economics, Taylor & Francis Journals, vol. 39(8), pages 943-946.

    Cited by:

    1. Spaenjers, C., 2011. "Essays in alternative investments," Other publications TiSEM 8c51041f-6a63-451f-b7f4-8, Tilburg University, School of Economics and Management.
    2. Dimson, E. & Spaenjers, C., 2009. "Ex-Post : The Investment Performance of Collectible Stamps," Other publications TiSEM 68b9952c-21e0-45b0-aeb7-d, Tilburg University, School of Economics and Management.

  92. Franses, Philip Hans & Kunst, Robert M., 2007. "Analyzing a panel of seasonal time series: Does seasonality in industrial production converge across Europe?," Economic Modelling, Elsevier, vol. 24(6), pages 954-968, November.

    Cited by:

    1. Herrerias, M.J., 2013. "Seasonal anomalies in electricity intensity across Chinese regions," Applied Energy, Elsevier, vol. 112(C), pages 1548-1557.
    2. Inchauspe, Julian & Li, Jun & Park, Jason, 2020. "Seasonal patterns of global oil consumption: Implications for long term energy policy," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 536-556.

  93. Fok, Dennis & Hans Franses, Philip & Paap, Richard, 2007. "Seasonality and non-linear price effects in scanner-data-based market-response models," Journal of Econometrics, Elsevier, vol. 138(1), pages 231-251, May.
    See citations under working paper version above.
  94. Koen Pauwels & Shuba Srinivasan & Philip Hans Franses, 2007. "When Do Price Thresholds Matter in Retail Categories?," Marketing Science, INFORMS, vol. 26(1), pages 83-100, 01-02.

    Cited by:

    1. Philipp Aschersleben & Winfried J. Steiner, 2022. "A semiparametric approach to estimating reference price effects in sales response models," Journal of Business Economics, Springer, vol. 92(4), pages 591-643, May.
    2. Casado, Esteban & Ferrer, Juan-Carlos, 2013. "Consumer price sensitivity in the retail industry: Latitude of acceptance with heterogeneous demand," European Journal of Operational Research, Elsevier, vol. 228(2), pages 418-426.
    3. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
    4. Thorsten Wiesel & Koen Pauwels & Joep Arts, 2011. "Practice Prize Paper --Marketing's Profit Impact: Quantifying Online and Off-line Funnel Progression," Marketing Science, INFORMS, vol. 30(4), pages 604-611, July.
    5. van Oest, Rutger, 2013. "Why are Consumers Less Loss Averse in Internal than External Reference Prices?," Journal of Retailing, Elsevier, vol. 89(1), pages 62-71.
    6. Guissoni, Leandro Angotti & Rodrigues, Jonny Mateus & Zambaldi, Felipe & Neves, Marcos Fava, 2021. "Distribution effectiveness through full- and self-service channels under economic fluctuations in an emerging market," Journal of Retailing, Elsevier, vol. 97(4), pages 545-560.
    7. Jean-Pierre H. Dubé, 2018. "Microeconometric Models of Consumer Demand," NBER Working Papers 25215, National Bureau of Economic Research, Inc.
    8. Nicole Koschate-Fischer & Katharina Wüllner, 2017. "New developments in behavioral pricing research," Journal of Business Economics, Springer, vol. 87(6), pages 809-875, August.
    9. Jung-Sup Bae & Weisheng Chiu & Sang-Back Nam, 2021. "Sport Fans’ Price Sensitivity Based on Loyalty Levels: A Case of Korean Professional Baseball League," Sustainability, MDPI, vol. 13(6), pages 1-13, March.
    10. Maarten Dossche & Freddy Heylen & Dirk Van den Poel, 2010. "The Kinked Demand Curve and Price Rigidity: Evidence from Scanner Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 112(4), pages 723-752, December.
    11. Villas-Boas, Sofia B & Bonnet, Celine, 2016. "Asymmetric Consumer Price Responses and Asymmetric Cost Pass-Through," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt172676f9, Department of Agricultural & Resource Economics, UC Berkeley.
    12. Bart J. Bronnenberg & Michael W. Kruger & Carl F. Mela, 2008. "—The IRI Marketing Data Set," Marketing Science, INFORMS, vol. 27(4), pages 745-748, 07-08.
    13. Richards, Timothy J. & Liaukonyte, Jura & Streletskaya, Nadia A., 2016. "Personalized pricing and price fairness," International Journal of Industrial Organization, Elsevier, vol. 44(C), pages 138-153.
    14. Marcial López-Pastor & Jesús García-Madariaga & Joaquín Sánchez & Jose Figueiredo, 2020. "Demand Impact for Prices Ending with “9” and “0” in Online and Offline Consumer Goods Retail Trade Channels," International Review of Management and Marketing, Econjournals, vol. 10(6), pages 58-78.
    15. Ngobo, Paul Valentin, 2011. "What Drives Household Choice of Organic Products in Grocery Stores?," Journal of Retailing, Elsevier, vol. 87(1), pages 90-100.
    16. Gijsenberg, Maarten J., 2014. "Going for gold: Investigating the (non)sense of increased advertising around major sports events," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 2-15.
    17. Bombaij, Nick J.F. & Gelper, Sarah & Dekimpe, Marnik G., 2022. "Designing successful temporary loyalty programs: An exploratory study on retailer and country differences," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1275-1295.
    18. Morlotti, Chiara & Mantin, Benny & Malighetti, Paolo & Redondi, Renato, 2024. "Price volatility of revenue managed goods: Implications for demand and price elasticity," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1039-1058.
    19. Michael Löffler, 2015. "Measuring willingness to pay: do direct methods work for premium durables?," Marketing Letters, Springer, vol. 26(4), pages 535-548, December.
    20. Ngobo, Paul-Valentin & Legohérel, Patrick & Guéguen, Nicolas, 2010. "A cross-category investigation into the effects of nine-ending pricing on brand choice," Journal of Retailing and Consumer Services, Elsevier, vol. 17(5), pages 374-385.
    21. Bogomolova, Svetlana & Dunn, Steven & Trinh, Giang & Taylor, Jennifer & Volpe, Richard J., 2015. "Price promotion landscape in the US and UK: Depicting retail practice to inform future research agenda," Journal of Retailing and Consumer Services, Elsevier, vol. 25(C), pages 1-11.
    22. Macé, Sandrine, 2012. "The Impact and Determinants of Nine-Ending Pricing in Grocery Retailing," Journal of Retailing, Elsevier, vol. 88(1), pages 115-130.
    23. Greg M. Allenby & Mark J. Garratt & Peter E. Rossi, 2010. "A Model for Trade-Up and Change in Considered Brands," Marketing Science, INFORMS, vol. 29(1), pages 40-56, 01-02.
    24. Cornelsen, Laura & Mazzocchi, Mario & Smith, Richard D., 2019. "Fat tax or thin subsidy? How price increases and decreases affect the energy and nutrient content of food and beverage purchases in Great Britain," Social Science & Medicine, Elsevier, vol. 230(C), pages 318-327.
    25. Lim, Leon Gim & Tuli, Kapil R. & Dekimpe, Marnik G., 2018. "Investors' evaluations of price-increase preannouncements," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 359-377.
    26. Sinha, Somesh Kumar & Verma, Priyanka, 2020. "Impact of sales Promotion's benefits on perceived value: Does product category moderate the results?," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    27. Richards, Timothy & Liaukonyte, Jura & Nadia, Streletskya, 2016. "Personalized Pricing and Price Fairness," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235809, Agricultural and Applied Economics Association.
    28. Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
    29. Ivan A. Guitart & Guillaume Hervet & Sarah Gelper, 2020. "Competitive advertising strategies for programmatic television," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 753-775, July.
    30. Leeflang, Peter S.H. & Bijmolt, Tammo H.A. & van Doorn, Jenny & Hanssens, Dominique M. & van Heerde, Harald J. & Verhoef, Peter C. & Wieringa, Jaap E., 2009. "Creating lift versus building the base: Current trends in marketing dynamics," International Journal of Research in Marketing, Elsevier, vol. 26(1), pages 13-20.
    31. de Haan, Evert & Wiesel, Thorsten & Pauwels, Koen, 2016. "The effectiveness of different forms of online advertising for purchase conversion in a multiple-channel attribution framework," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 491-507.
    32. Timothy J. Richards & Miguel I. Gómez & Iryna Printezis, 2016. "Hysteresis, Price Acceptance, and Reference Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 679-706.
    33. van Donselaar, K.H. & Peters, J. & de Jong, A. & Broekmeulen, R.A.C.M., 2016. "Analysis and forecasting of demand during promotions for perishable items," International Journal of Production Economics, Elsevier, vol. 172(C), pages 65-75.
    34. KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Business and Economics.
    35. Beneke, Justin & Carter, Stephen, 2015. "The development of a consumer value proposition of private label brands and the application thereof in a South African retail context," Journal of Retailing and Consumer Services, Elsevier, vol. 25(C), pages 22-35.
    36. Otto, Philipp E. & Schmidt, Lennard, 2021. "Reservation price uncertainty: Loss, virtue, or emotional heterogeneity?," Journal of Economic Psychology, Elsevier, vol. 87(C).
    37. Foxall, Gordon R. & Yan, Ji & Oliveira-Castro, Jorge M. & Wells, Victoria K., 2013. "Brand-related and situational influences on demand elasticity," Journal of Business Research, Elsevier, vol. 66(1), pages 73-81.
    38. Kiygi Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2012. "The effectiveness of high-frequency direct-response commercials," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 98-109.
    39. Chen Wei & Sobhan Asian & Gurdal Ertek & Zhi-Hua Hu, 2020. "Location-based pricing and channel selection in a supply chain: a case study from the food retail industry," Annals of Operations Research, Springer, vol. 291(1), pages 959-984, August.
    40. Woodside, Arch G. & Ozcan, Timucin, 2009. "Customer choices of manufacturer versus retailer brands in alternative price and usage contexts," Journal of Retailing and Consumer Services, Elsevier, vol. 16(2), pages 100-108.
    41. Kopalle, Praveen K. & Pauwels, Koen & Akella, Laxminarayana Yashaswy & Gangwar, Manish, 2023. "Dynamic pricing: Definition, implications for managers, and future research directions," Journal of Retailing, Elsevier, vol. 99(4), pages 580-593.
    42. ter Braak, Anne & Deleersnyder, Barbara & Geyskens, Inge & Dekimpe, Marnik G., 2013. "Does private-label production by national-brand manufacturers create discounter goodwill?," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 343-357.
    43. Gauri, Dinesh K. & Ratchford, Brian & Pancras, Joseph & Talukdar, Debabrata, 2017. "An Empirical Analysis of the Impact of Promotional Discounts on Store Performance," Journal of Retailing, Elsevier, vol. 93(3), pages 283-303.
    44. Eckert, C. & J. Hohberger (Jan) & Franses, Ph.H.B.F., 2022. "Gaussian Copula Regression in the Presence of Thresholds," Econometric Institute Research Papers 2022-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    45. Lillian L. Cheng & Kent B. Monroe, 2013. "An appraisal of behavioral price research (part 1): price as a physical stimulus," AMS Review, Springer;Academy of Marketing Science, vol. 3(3), pages 103-129, September.
    46. Dekimpe, Marnik G., 2020. "Retailing and retailing research in the age of big data analytics," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 3-14.
    47. Kalyanaram, Gurumurthy & Winer, Russell S., 2022. "Behavioral response to price: Data-based insights and future research for retailing," Journal of Retailing, Elsevier, vol. 98(1), pages 46-70.

  95. Bijwaard, Govert E. & Franses, Philip Hans & Paap, Richard, 2006. "Modeling Purchases as Repeated Events," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 487-502, October.
    See citations under working paper version above.
  96. Hyung, Namwon & Franses, Philip Hans & Penm, Jack, 2006. "Structural breaks and long memory in US inflation rates: Do they matter for forecasting?," Research in International Business and Finance, Elsevier, vol. 20(1), pages 95-110, March.
    See citations under working paper version above.
  97. H. Peter Boswijk & Philip Hans Franses, 2006. "Robust Inference on Average Economic Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 345-370, June.
    See citations under working paper version above.
  98. Philip Hans Franses & Dick van Dijk, 2006. "A simple test for PPP among traded goods," Applied Financial Economics, Taylor & Francis Journals, vol. 16(1-2), pages 19-27.
    See citations under working paper version above.
  99. Philip Hans Franses, 2006. "On modeling panels of time series," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(4), pages 438-456, November.
    See citations under working paper version above.
  100. Gerard J. Tellis & Philip Hans Franses, 2006. "Optimal Data Interval for Estimating Advertising Response," Marketing Science, INFORMS, vol. 25(3), pages 217-229, 05-06.

    Cited by:

    1. Chen, Chien-Ming & Chuang, Howard Hao-Chun, 2023. "Time to shift the shift: Performance effects of within-day cumulative service encounters in retail stores," Omega, Elsevier, vol. 119(C).
    2. Leon A. Petrosyan & David W.K. Yeung, 2020. "Cooperative Dynamic Games with Durable Controls: Theory and Application," Dynamic Games and Applications, Springer, vol. 10(4), pages 872-896, December.
    3. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    4. Hee Mok Park & Joseph Pancras, 2022. "Social and Spatiotemporal Impacts of Casino Jackpot Events," Marketing Science, INFORMS, vol. 41(3), pages 575-592, May.
    5. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    6. van Dieijen, M.J. & Borah, A. & Tellis, G.J. & Franses, Ph.H.B.F., 2016. "Volatility Spillovers Across User-Generated Content and Stock Market Performance," ERIM Report Series Research in Management ERS-2016-008-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Somayeh Moazeni & Boris Defourny & Monika J. Wilczak, 2020. "Sequential Learning in Designing Marketing Campaigns for Market Entry," Management Science, INFORMS, vol. 66(9), pages 4226-4245, September.
    8. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2021. "Forecasting time-varying arrivals: Impact of direct response advertising on call center performance," Journal of Business Research, Elsevier, vol. 131(C), pages 227-240.
    9. Rex Yuxing Du & Mingyu Joo & Kenneth C. Wilbur, 2019. "Advertising and brand attitudes: Evidence from 575 brands over five years," Quantitative Marketing and Economics (QME), Springer, vol. 17(3), pages 257-323, September.
    10. Rex Yuxing Du & Mingyu Joo & Kenneth C. Wilbur, 2018. "Advertising and Brand Attitudes: Evidence from 575 Brands over Five Years," Papers 1810.07783, arXiv.org.
    11. Guitart, Ivan A. & Hervet, Guillaume, 2017. "The impact of contextual television ads on online conversions: An application in the insurance industry," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 480-498.
    12. Yan Lu & Debanjan Mitra & David Musto & Sugata Ray, 2020. "Can Brands Circumvent Marketing Regulations? Exploiting Umbrella Branding in Financial Markets," Marketing Science, INFORMS, vol. 39(1), pages 71-91, January.
    13. Ashish Sood & Gareth M. James & Gerard J. Tellis, 2009. "Functional Regression: A New Model for Predicting Market Penetration of New Products," Marketing Science, INFORMS, vol. 28(1), pages 36-51, 01-02.
    14. Tom Coupe & Natalia Chaban, 2020. "Creating Europe through culture? The impact of the European Song Contest on European identity," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 885-908, November.
    15. Ashwin Aravindakshan & Prasad A. Naik, 2015. "Understanding the Memory Effects in Pulsing Advertising," Operations Research, INFORMS, vol. 63(1), pages 35-47, February.
    16. de Haan, Evert & Wiesel, Thorsten & Pauwels, Koen, 2016. "The effectiveness of different forms of online advertising for purchase conversion in a multiple-channel attribution framework," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 491-507.
    17. Sood, Ashish & Kappe, Eelco & Stremersch, Stefan, 2014. "The commercial contribution of clinical studies for pharmaceutical drugs," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 65-77.
    18. Tirunillai, S. & Tellis, G.J., 2011. "Does Online Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," ERIM Report Series Research in Management 25817, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. Seshadri Tirunillai & Gerard J. Tellis, 2012. "Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," Marketing Science, INFORMS, vol. 31(2), pages 198-215, March.
    20. Kiygi Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2012. "The effectiveness of high-frequency direct-response commercials," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 98-109.
    21. Zizhuo Wang & Chaolin Yang & Hongsong Yuan & Yaowu Zhang, 2021. "Aggregation Bias in Estimating Log‐Log Demand Function," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 3906-3922, November.
    22. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2017. "Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 90-101.
    23. Mingyung Kim & Eric T. Bradlow & Raghuram Iyengar, 2022. "Selecting Data Granularity and Model Specification Using the Scaled Power Likelihood with Multiple Weights," Marketing Science, INFORMS, vol. 41(4), pages 848-866, July.
    24. Eelco Kappe & Ashley Stadler Blank & Wayne S. DeSarbo, 2014. "A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions," Management Science, INFORMS, vol. 60(6), pages 1489-1510, June.
    25. Eckert, C. & J. Hohberger (Jan) & Franses, Ph.H.B.F., 2022. "Gaussian Copula Regression in the Presence of Thresholds," Econometric Institute Research Papers 2022-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. ten Cate, Arie & Franses, Philip Hans, 2008. "Error-correction modelling in discrete and continuous time," Economics Letters, Elsevier, vol. 101(2), pages 140-141, November.
    27. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2010. "To Aggregate or Not to Aggregate: Should decisions and models have the same frequency?," ERIM Report Series Research in Management ERS-2010-046-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    28. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.
    29. Lizhen Xu & Jason A. Duan & Andrew Whinston, 2014. "Path to Purchase: A Mutually Exciting Point Process Model for Online Advertising and Conversion," Management Science, INFORMS, vol. 60(6), pages 1392-1412, June.

  101. Richard Paap & Philip Hans Franses & Bas Donkers & Jedid-Jah Jonker, 2006. "Deriving target selection rules from endogenously selected samples," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 549-562.
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  102. Philip Hans Franses & Namwon Hyung, 2005. "Forecasting time series with long memory and level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 1-16.

    Cited by:

    1. Dominique Guegan, 2008. "Non-stationarity and meta-distribution," Post-Print halshs-00270708, HAL.
    2. Dominique Guegan, 2007. "Global and local stationary modelling in finance: theory and empirical evidence," Post-Print halshs-00187875, HAL.
    3. Dominique Guegan & Zhiping Lu, 2007. "A note on self-similarity for discrete time series," Post-Print halshs-00187910, HAL.
    4. Franses, Philip Hans & Janssens, Eva, 2018. "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 261-292.
    5. Terence C. Mills, 2007. "Time series modelling of two millennia of northern hemisphere temperatures: long memory or shifting trends?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(1), pages 83-94, January.

  103. Koning, Alex J. & Franses, Philip Hans & Hibon, Michele & Stekler, H.O., 2005. "The M3 competition: Statistical tests of the results," International Journal of Forecasting, Elsevier, vol. 21(3), pages 397-409.

    Cited by:

    1. Armstrong, J. Scott, 2007. "Significance Tests Harm Progress in Forecasting," MPRA Paper 81664, University Library of Munich, Germany.
    2. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    3. Kang, Yanfei & Spiliotis, Evangelos & Petropoulos, Fotios & Athiniotis, Nikolaos & Li, Feng & Assimakopoulos, Vassilios, 2021. "Déjà vu: A data-centric forecasting approach through time series cross-similarity," Journal of Business Research, Elsevier, vol. 132(C), pages 719-731.
    4. Gorr, Wilpen L. & Schneider, Matthew J., 2013. "Large-change forecast accuracy: Reanalysis of M3-Competition data using receiver operating characteristic analysis," International Journal of Forecasting, Elsevier, vol. 29(2), pages 274-281.
    5. Zhang, Bohan & Panagiotelis, Anastasios & Kang, Yanfei, 2024. "Discrete forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 318(1), pages 143-153.
    6. Van Belle, Jente & Crevits, Ruben & Verbeke, Wouter, 2023. "Improving forecast stability using deep learning," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1333-1350.
    7. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    8. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios & Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "The M5 uncertainty competition: Results, findings and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1365-1385.
    9. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    10. Jeon, Jooyoung & Panagiotelis, Anastasios & Petropoulos, Fotios, 2019. "Probabilistic forecast reconciliation with applications to wind power and electric load," European Journal of Operational Research, Elsevier, vol. 279(2), pages 364-379.
    11. Ortega, Luz C. & Otero, Luis Daniel & Solomon, Mitchell & Otero, Carlos E. & Fabregas, Aldo, 2023. "Deep learning models for visibility forecasting using climatological data," International Journal of Forecasting, Elsevier, vol. 39(2), pages 992-1004.
    12. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
    13. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    14. Xiaoqian Wang & Yanfei Kang & Rob J Hyndman & Feng Li, 2020. "Distributed ARIMA Models for Ultra-long Time Series," Monash Econometrics and Business Statistics Working Papers 29/20, Monash University, Department of Econometrics and Business Statistics.
    15. Chelsey Hill & James Li & Matthew J. Schneider & Martin T. Wells, 2021. "The tensor auto‐regressive model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 636-652, July.
    16. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    17. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    18. Chan, Chi Kin & Witt, Stephen F. & Lee, Y.C.E. & Song, H., 2010. "Tourism forecast combination using the CUSUM technique," Tourism Management, Elsevier, vol. 31(6), pages 891-897.
    19. Christoph Bergmeir & Rob J Hyndman & Jose M Benitez, 2014. "Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation," Monash Econometrics and Business Statistics Working Papers 11/14, Monash University, Department of Econometrics and Business Statistics.
    20. Petropoulos, Fotios & Wang, Xun & Disney, Stephen M., 2019. "The inventory performance of forecasting methods: Evidence from the M3 competition data," International Journal of Forecasting, Elsevier, vol. 35(1), pages 251-265.
    21. Chiew, Ernest & Choong, Shin Siang, 2022. "A solution for M5 Forecasting - Uncertainty: Hybrid gradient boosting and autoregressive recurrent neural network for quantile estimation," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1442-1447.
    22. Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011. "Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660.
    23. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
    24. Ord, Keith, 2007. "Comments on "significance tests harm progress in forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 331-332.
    25. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "M5 accuracy competition: Results, findings, and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1346-1364.
    26. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2023. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Papers 2401.00249, arXiv.org, revised Jul 2024.
    27. Evangelos Spiliotis & Spyros Makridakis & Artemios-Anargyros Semenoglou & Vassilios Assimakopoulos, 2022. "Comparison of statistical and machine learning methods for daily SKU demand forecasting," Operational Research, Springer, vol. 22(3), pages 3037-3061, July.
    28. Ma, Shaohui & Fildes, Robert, 2021. "Retail sales forecasting with meta-learning," European Journal of Operational Research, Elsevier, vol. 288(1), pages 111-128.
    29. Villegas, Marco A. & Pedregal, Diego J., 2019. "Automatic selection of unobserved components models for supply chain forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 157-169.
    30. Taylor, James W. & Taylor, Kathryn S., 2023. "Combining probabilistic forecasts of COVID-19 mortality in the United States," European Journal of Operational Research, Elsevier, vol. 304(1), pages 25-41.
    31. Spiliotis, Evangelos & Assimakopoulos, Vassilios & Makridakis, Spyros, 2020. "Generalizing the Theta method for automatic forecasting," European Journal of Operational Research, Elsevier, vol. 284(2), pages 550-558.
    32. Ulrich, Matthias & Jahnke, Hermann & Langrock, Roland & Pesch, Robert & Senge, Robin, 2022. "Classification-based model selection in retail demand forecasting," International Journal of Forecasting, Elsevier, vol. 38(1), pages 209-223.
    33. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    34. Tuominen, Jalmari & Pulkkinen, Eetu & Peltonen, Jaakko & Kanniainen, Juho & Oksala, Niku & Palomäki, Ari & Roine, Antti, 2024. "Forecasting emergency department occupancy with advanced machine learning models and multivariable input," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1410-1420.
    35. Kathryn S Taylor & James W Taylor, 2022. "Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-25, March.
    36. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
    37. Girolimetto, Daniele & Athanasopoulos, George & Di Fonzo, Tommaso & Hyndman, Rob J., 2024. "Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1134-1151.
    38. Kang, Yanfei & Cao, Wei & Petropoulos, Fotios & Li, Feng, 2022. "Forecast with forecasts: Diversity matters," European Journal of Operational Research, Elsevier, vol. 301(1), pages 180-190.
    39. Di Fonzo, Tommaso & Girolimetto, Daniele, 2023. "Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives," International Journal of Forecasting, Elsevier, vol. 39(1), pages 39-57.
    40. Meira, Erick & Cyrino Oliveira, Fernando Luiz & Jeon, Jooyoung, 2021. "Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals," International Journal of Forecasting, Elsevier, vol. 37(2), pages 547-568.
    41. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    42. Fiorucci, Jose A. & Pellegrini, Tiago R. & Louzada, Francisco & Petropoulos, Fotios & Koehler, Anne B., 2016. "Models for optimising the theta method and their relationship to state space models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1151-1161.
    43. Svetunkov, Ivan & Chen, Huijing & Boylan, John E., 2023. "A new taxonomy for vector exponential smoothing and its application to seasonal time series," European Journal of Operational Research, Elsevier, vol. 304(3), pages 964-980.
    44. Di Fonzo, Tommaso & Girolimetto, Daniele, 2024. "Forecast combination-based forecast reconciliation: Insights and extensions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 490-514.
    45. Willem P Sijp & Anastasios Panagiotelis, 2024. "Estimating granular house price distributions in the Australian market using Gaussian mixtures," Papers 2404.05178, arXiv.org.
    46. Sarmas, Elissaios & Spiliotis, Evangelos & Stamatopoulos, Efstathios & Marinakis, Vangelis & Doukas, Haris, 2023. "Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models," Renewable Energy, Elsevier, vol. 216(C).
    47. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    48. Spiliotis, Evangelos & Makridakis, Spyros & Kaltsounis, Anastasios & Assimakopoulos, Vassilios, 2021. "Product sales probabilistic forecasting: An empirical evaluation using the M5 competition data," International Journal of Production Economics, Elsevier, vol. 240(C).
    49. Giacomo Sbrana & Andrea Silvestrini, 2024. "The structural Theta method and its predictive performance in the M4-Competition," Temi di discussione (Economic working papers) 1457, Bank of Italy, Economic Research and International Relations Area.
    50. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    51. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
    52. Ma, Shaohui & Fildes, Robert, 2020. "Forecasting third-party mobile payments with implications for customer flow prediction," International Journal of Forecasting, Elsevier, vol. 36(3), pages 739-760.
    53. Kourentzes, Nikolaos, 2014. "On intermittent demand model optimisation and selection," International Journal of Production Economics, Elsevier, vol. 156(C), pages 180-190.
    54. Davide Provenzano & Serena Volo, 2022. "Tourism recovery amid COVID-19: The case of Lombardy, Italy," Tourism Economics, , vol. 28(1), pages 110-130, February.
    55. Eren Bas & Erol Egrioglu & Ufuk Yolcu, 2021. "Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm," Forecasting, MDPI, vol. 3(4), pages 1-11, November.
    56. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    57. Stekler, H.O., 2007. "Significance tests harm progress in forecasting: Comment," International Journal of Forecasting, Elsevier, vol. 23(2), pages 329-330.
    58. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.
    59. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
    60. Robert R. Andrawis & Amir F. Atiya, 2009. "A new Bayesian formulation for Holt's exponential smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 218-234.

  104. Paap, Richard & Franses, Philip Hans & van Dijk, Dick, 2005. "Does Africa grow slower than Asia, Latin America and the Middle East? Evidence from a new data-based classification method," Journal of Development Economics, Elsevier, vol. 77(2), pages 553-570, August.

    Cited by:

    1. Rosa Bernardini Papalia & Silvia Bertarelli, 2013. "Nonlinearities in economic growth and club convergence," Empirical Economics, Springer, vol. 44(3), pages 1171-1202, June.
    2. Ferreira Paulo & Dionísio Andreia, 2016. "GDP growth and convergence determinants in the European Union: a crisp-set analysis," Review of Economic Perspectives, Sciendo, vol. 16(4), pages 279-296, December.
    3. Ann L. Owen & Julio Videras, 2016. "Classifying Human Development with Latent Class Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(3), pages 959-981, July.
    4. Tim Salimans, 2011. "Variable Selection and Functional Form Uncertainty in Cross-Country Growth Regressions," Tinbergen Institute Discussion Papers 11-012/4, Tinbergen Institute.
    5. Guanchun Liu & Shichang Ma & Chien‐Chiang Lee & Ming Xu, 2020. "Growth decomposition bias when accounting for heterogeneous regimes: Evidence from China," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 691-711, May.
    6. Walheer, Barnabé, 2016. "Growth and convergence of the OECD countries: A multi-sector production-frontier approach," European Journal of Operational Research, Elsevier, vol. 252(2), pages 665-675.
    7. Serge Rey & Florent Deisting, 2012. "GDP per Capita among African Countries over the Period 1950-2008: Highlights of Convergence Clubs," Post-Print hal-01881912, HAL.
    8. Ann Owen & Julio Videras & Lewis Davis, 2009. "Do all countries follow the same growth process?," Journal of Economic Growth, Springer, vol. 14(4), pages 265-286, December.
    9. Kerekes, Monika, 2012. "Growth miracles and failures in a Markov switching classification model of growth," Journal of Development Economics, Elsevier, vol. 98(2), pages 167-177.
    10. Owen, Ann L. & Temesvary, Judit, 2012. "Foreign lending, local lending, and economic growth," MPRA Paper 39978, University Library of Munich, Germany.
    11. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Gianfranco Di Vaio & Kerstin Enflo, 2010. "Did Globalization Drive Convergence? Identifying Cross-Country Growth Regimes in the Long Run," Working Paper series 30_10, Rimini Centre for Economic Analysis.
    13. Castellacci, Fulvio, 2008. "Technology clubs, technology gaps and growth trajectories," Structural Change and Economic Dynamics, Elsevier, vol. 19(4), pages 301-314, December.
    14. Deng, Wen-Shuenn & Lin, Yi-Chen & Gong, Jinguo, 2012. "A smooth coefficient quantile regression approach to the social capital–economic growth nexus," Economic Modelling, Elsevier, vol. 29(2), pages 185-197.
    15. Amélie Charles & Olivier Darne & Jean-François Hoarau, 2012. "Convergence of real per capita GDP within COMESA countries: A panel unit root evidence," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(1), pages 53-71, August.
    16. Michelle Gilmartin & Dimitris Korobilis, 2012. "On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 59(2), pages 179-195, May.
    17. Bram van Dijk & Philip Hans Franses & Richard Paap & Dick van Dijk, 2011. "Modelling regional house prices," Applied Economics, Taylor & Francis Journals, vol. 43(17), pages 2097-2110.
    18. Michele Battisti & Christopher F. Parmeter, 2011. "Income Polarization, Convergence Tools and Mixture Analysis," Working Papers 2011-17, University of Miami, Department of Economics.
    19. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2010. "Does the real GDP per capita convergence hold in the Common Market for Eastern and Southern Africa?," Post-Print hal-00797485, HAL.
    20. Ntombiyesibini Matonana & Andrew Phiri, 2020. "Convergence Dynamics between South Africa and Her Main Trading Partners," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 18(1 (Spring), pages 25-44.
    21. David Audretsch & Mark Sanders & Lu Zhang, 2021. "International product life cycles, trade and development stages," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1630-1673, October.
    22. Phillips, Kerk L. & Chen, Baizhu, 2011. "Regional growth in China: An empirical investigation using multiple imputation and province-level panel data," Research in Economics, Elsevier, vol. 65(3), pages 243-253, September.
    23. Jerzmanowski, Michal, 2006. "Empirics of hills, plateaus, mountains and plains: A Markov-switching approach to growth," Journal of Development Economics, Elsevier, vol. 81(2), pages 357-385, December.
    24. Zheng Ying & Chang-Rui Dong & Hsu-Ling Chang & Chi-Wei Su, 2014. "Are Real GDP Levels Stationary in African Countries?," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 392-401, September.
    25. Basturk, N. & Paap, R. & van Dijk, D.J.C., 2010. "Financial Development and Convergence Clubs," Econometric Institute Research Papers EI 2010-52, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Barnabé Walheer, 2016. "Multi-Sector Nonparametric Production-Frontier Analysis of the Economic Growth and the Convergence of the European Countries," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 498-524, October.
    27. Becchetti, L. & Corrado, L. & Rossetti , F., 2008. "Easterlin-types and Frustrated Achievers: the Heterogeneous Effects of Income Changes on Life Satisfaction," Cambridge Working Papers in Economics 0816, Faculty of Economics, University of Cambridge.
    28. Pérez-Urdiales, María & Baerenklau, Kenneth A., 2019. "Learning to live within your (water) budget: Evidence from allocation-based rates," Resource and Energy Economics, Elsevier, vol. 57(C), pages 205-221.
    29. Eberhardt, Markus & Teal, Francis, 2009. "Econometrics for Grumblers: A New Look at the Literature on Cross-Country Growth Empirics," MPRA Paper 15813, University Library of Munich, Germany.
    30. Morier, Bruno & Teles, Vladimir Kühl, 2016. "A Time-Varying Markov-Switching Model For Economic Growth," Macroeconomic Dynamics, Cambridge University Press, vol. 20(6), pages 1550-1580, September.
    31. Guanchun Liu & Yuanyuan Liu & Chien-Chiang Lee, 2020. "Growth Sources of Green Economy and Energy Consumption in China: New Evidence Accounting for Heterogeneous Regimes," The Energy Journal, , vol. 41(6), pages 33-64, November.
    32. Tedesco, Ilaria & Pelloni, Alessandra & Trovato, Giovanni, 2015. "Oecd Agricultural Subsidies And Poverty Rates In Lower Income Countries," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(2), pages 1-19, April.
    33. Gianfranco Di Vaio & Kerstin Enflo, 2009. "Did Globalization Lead to Segmentation? Identifying Cross-Country Growth Regimes in the Long-Run," Discussion Papers 09-08, University of Copenhagen. Department of Economics.
    34. Yuki, Kazuhiro, 2012. "Education, inequality, and development in a dual economy," MPRA Paper 39062, University Library of Munich, Germany.
    35. Vidoli, Francesco & Pignataro, Giacomo & Benedetti, Roberto, 2022. "Identification of spatial regimes of the production function of Italian hospitals through spatially constrained cluster-wise regression," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    36. Rodríguez, Francisco & Shelton, Cameron A., 2013. "Cleaning up the kitchen sink: Specification tests and average derivative estimators for growth econometrics," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 260-273.
    37. Michele Battisti & Christopher F. Parmeter, 2010. "Convergence Tools and Mixture Analysis," Working Papers CELEG 1007, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    38. Owen, Ann L. & Temesvary, Judit, 2014. "Heterogeneity in the growth and finance relationship: How does the impact of bank finance vary by country and type of lending?," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 275-288.
    39. Laura Serrano & Antonio Sianes & Antonio Ariza-Montes, 2020. "Understanding the Implementation of Airbnb in Urban Contexts: Towards a Categorization of European Cities," Land, MDPI, vol. 9(12), pages 1-21, December.
    40. Nalan Baştürk & Richard Paap & Dick van Dijk, 2012. "Structural differences in economic growth: an endogenous clustering approach," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 119-134, January.
    41. Guanchun Liu & Chien-Chiang Lee & Yuanyuan Liu, 2020. "Growth path heterogeneity across provincial economies in China: the role of geography versus institutions," Empirical Economics, Springer, vol. 59(2), pages 503-546, August.
    42. Owen, Ann L. & Videras, Julio, 2012. "The quality of growth," MPRA Paper 38342, University Library of Munich, Germany.
    43. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827.
    44. Marco Alfo & Giovanni Trovato & Robert J. Waldmann, 2008. "Testing for country heterogeneity in growth models using a finite mixture approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 487-514.
    45. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.
    46. Antonio Sianes & Luis A. Fernández-Portillo & Adela Toscano-Valle & Elena Pérez-Velasco, 2023. "Heterogeneity in financing for development strategies as a hindering factor to achieve a global agreement on the 2030 Agenda," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    47. Arye Hillman, 2007. "Economic and security consequences of supreme values," Public Choice, Springer, vol. 131(3), pages 259-280, June.
    48. Richard Startz, 2020. "The next hundred years of growth and convergence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 99-113, January.
    49. Chris Papageorgiou & Winford H. Masanjala, 2006. "Initial Conditions, European Colonialism and Africa's Growth," Departmental Working Papers 2006-01, Department of Economics, Louisiana State University.
    50. Kerekes, Monika, 2009. "Growth miracles and failures in a Markov switching classification model of growth," Discussion Papers 2009/11, Free University Berlin, School of Business & Economics.
    51. Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.

  105. Vogelsang, Timothy J. & Franses, Philip Hans, 2005. "Testing for common deterministic trend slopes," Journal of Econometrics, Elsevier, vol. 126(1), pages 1-24, May.
    See citations under working paper version above.
  106. Franses, Philip Hans & van Dijk, Dick, 2005. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," International Journal of Forecasting, Elsevier, vol. 21(1), pages 87-102.
    See citations under working paper version above.
  107. Ben Pelzer & Rob Eisinga & Philip Franses, 2005. "“Panelizing” Repeated Cross Sections," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(2), pages 155-174, April.

    Cited by:

    1. Spagnoli, Paola & Caetano, Antonio & Santos, Susana Correia, 2012. "Satisfaction with job aspects: Do patterns change over time?," Journal of Business Research, Elsevier, vol. 65(5), pages 609-616.

  108. Albert C. Bemmaor & Philip Hans Franses, 2005. "The diffusion of marketing science in the practitioners' community: opening the black box," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(4‐5), pages 289-301, July.

    Cited by:

    1. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.

  109. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 785-794.
    See citations under working paper version above.
  110. Philip Hans Franses & Herman K. van Dijk & Dick van Dijk, 2005. "On the dynamics of business cycle analysis: editors' introduction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 147-150.

    Cited by:

    1. Kevin Lee & Anthony Garratt & Kalvinder Shields, 2009. "Decision Making in hard Times: What is a Recession, Why Do We Care and How Do We Know When We Are in One?," Discussion Papers in Economics 09/22, Division of Economics, School of Business, University of Leicester.
    2. Ooms, M., 2008. "Trends in Applied Econometrics Software Development 1985-2008, an analysis of Journal of Applied Econometrics research articles, software reviews, data and code," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    3. Garratt, Anthony & Lee, Kevin & Shields, Kalvinder, 2016. "Forecasting global recessions in a GVAR model of actual and expected output," International Journal of Forecasting, Elsevier, vol. 32(2), pages 374-390.
    4. Anthony Garratt & Kevin Lee & Kalvinder Shields, 2014. "Forecasting Global Recessions in a GVAR Model of Actual and Expected Output in the G7," Discussion Papers 2014/06, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    5. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2006. "Não Linearidade Nos Ciclos De Negócios: Modelo Auto-Regressivo “Smooth Transition” Para O Índice Geral De Produção Industrial Brasileiro E Bens De Capital," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 10, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6. Kevin Lee & Kalvinder Shields, 2010. "Decision-Making in Hard Times: What is a Recession, Why Do We Care and When Do We Know We Are in One?," Discussion Papers 10/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).

  111. Paap, Richard & van Nierop, Erjen & van Heerde, Harald J. & Wedel, Michel & Franses, Philip Hans & Alsem, Karel Jan, 2005. "Consideration sets, intentions and the inclusion of "don't know" in a two-stage model for voter choice," International Journal of Forecasting, Elsevier, vol. 21(1), pages 53-71.
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  112. Paulo Rodrigues & Philip Hans Franses, 2005. "A sequential approach to testing seasonal unit roots in high frequency data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 555-569.
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  113. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827.

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    1. Maha Kalai & Nahed Zghidi, 2019. "Foreign Direct Investment, Trade, and Economic Growth in MENA Countries: Empirical Analysis Using ARDL Bounds Testing Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 397-421, March.
    2. Jude Eggoh & Chrysost Bangake & Gervasio Semedo, 2018. "Do remittances spur economic growth? Evidence from developing countries," Post-Print hal-02107277, HAL.
    3. Ben Hmiden, Oussama & Ben Cheikh, Nidhaleddine, 2016. "Debt-threshold effect in sovereign credit ratings: New evidence from nonlinear panel smooth transition models," Finance Research Letters, Elsevier, vol. 19(C), pages 273-278.
    4. Yongsung Chang & Sunoong Hwang, 2011. "Asymmetric Phase Shifts in the U.S. Industrial Production Cycles," RCER Working Papers 564, University of Rochester - Center for Economic Research (RCER).
    5. Cristina Jude & Gregory Levieuge, 2017. "Growth Effect of Foreign Direct Investment in Developing Economies: The Role of Institutional Quality," Post-Print hal-03557767, HAL.
    6. Wafa Ghardallou & Abdelkader Boudriga, 2014. "Financial Development and Democracy: is the Relationship Non-Linear?," Working Papers 886, Economic Research Forum, revised Dec 2014.
    7. Cristina JUDE & Grégory LEVIEUGE, 2013. "Growth Effect of FDI in Developing Economies: the Role of Institutional Quality," LEO Working Papers / DR LEO 2251, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    8. Hermann Ndoya hegueu & Aristophane Djeufack dongmo, 2021. "Urbanization, Governance and Informal Economy: an African Tale," Economics Bulletin, AccessEcon, vol. 41(3), pages 1525-1540.
    9. Djedje Hermann Yohou & Michaël Goujon & Wautabouna Ouattara, 2015. "Heterogeneous Aid Effects on Tax Revenues: Accounting for Government Stability in WAEMU Countries," Working Papers halshs-01138159, HAL.
    10. Wafa Ghardallou & Noha Alessa, 2022. "Corporate Social Responsibility and Firm Performance in GCC Countries: A Panel Smooth Transition Regression Model," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    11. Eggoh, Jude C. & Khan, Muhammad, 2014. "On the nonlinear relationship between inflation and economic growth," Research in Economics, Elsevier, vol. 68(2), pages 133-143.
    12. Chi-Hui Wang & Prasad Padmanabhan & Chia-Hsing Huang, 2021. "The Impact of Renewable Energy, Urbanization, and Environmental Sustainability Ratings on the Environmental Kuznets Curve and the Pollution Haven Hypothesis," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    13. Shiao-Yen Liu & Po-Chin Wu & Tsai-Yuan Huang, 2018. "Nonlinear Causality between Education and Health: the Role of Human Development Index," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 13(3), pages 761-777, September.
    14. Olivier Damette & Mathilde Maurel & Michael A. Stemmer, 2016. "What does it take to grow out of recession? An error-correction approach towards growth convergence of European and transition countries," Post-Print halshs-01318131, HAL.
    15. Gomes, Gabriel & Hache, Emmanuel & Mignon, Valérie & Paris, Anthony, 2018. "On the current account - biofuels link in emerging and developing countries: do oil price fluctuations matter?," Energy Policy, Elsevier, vol. 116(C), pages 60-67.
    16. Tuomas A. Peltonen & Adina Popescu & Michael Sager, 2011. "Can non‐linear real shocks explain the persistence of PPP exchange rate disequilibria?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 16(3), pages 290-306, July.
    17. Li, Wenying & Dorfman, Jeffrey H., 2019. "The implications of heterogeneous habit in consumer beverage purchases on soda and sin taxes," Food Policy, Elsevier, vol. 84(C), pages 111-120.
    18. Gabriella Legrenzi & Costas Milas, 2012. "Long-Run Debt Sustainability and Threshold Adjustments: Non-Linear Empirical Evidence from the GIIPS," Economics Bulletin, AccessEcon, vol. 32(3), pages 2586-2593.
    19. Henry Aray & Luis Pedagua, 2021. "Decentralization and economic growth: Evidence across states of some relevant macroeconomic variables," ThE Papers 21/08, Department of Economic Theory and Economic History of the University of Granada..
    20. Artur Tarassow, 2015. "Financial Investment Constraints. A Panel Threshold Application to German Firm Level Data," Macroeconomics and Finance Series 201405, University of Hamburg, Department of Socioeconomics.
    21. Audrey Allegret Sallenave & Jean-Pierre Allegret, 2019. "Did Foreign Exchange Holding Influence Growth Performance During the Global Financial Crisis?," Post-Print hal-03573567, HAL.
    22. Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "International R&D spillovers, absorptive capacity and relative backwardness: a panel smooth transition regression model," Department of Economics Working Papers 1203, Department of Economics, University of Trento, Italia.
    23. Furceri, Davide & Loungani, Prakash, 2018. "The distributional effects of capital account liberalization," Journal of Development Economics, Elsevier, vol. 130(C), pages 127-144.
    24. Nicholas Apergis, 2015. "Economic freedom and income inequality: further evidence from 58 countries in the long-run," Financial Theory and Practice, Institute of Public Finance, vol. 39(4), pages 349-370.
    25. Antonia López‐Villavicencio & José Ignacio Silva, 2011. "Employment Protection And The Non‐Linear Relationship Between The Wage‐Productivity Gap And Unemployment," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(2), pages 200-220, May.
    26. Juan Carlos Cuestas & Estefanía Mourelle & Paulo José Regis, 2020. "Real exchange rate misalignments in CEECs: Have they hindered growth?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 733-756, November.
    27. Tue Gørgens & Christopher L. Skeels & Allan H. Würtz, 2009. "Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models," CREATES Research Papers 2009-51, Department of Economics and Business Economics, Aarhus University.
    28. Myung Hwan Seo & Yongcheol Shin, 2014. "Dynamic Panels with Threshold Effect and Endogeneity," STICERD - Econometrics Paper Series 577, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    29. Khezri, Mohsen & Mamkhezri, Jamal & Heshmati, Almas, 2024. "Exploring non-linear causal nexus between economic growth and energy consumption across various R&D regimes: Cross-country evidence from a PSTR model," Energy Economics, Elsevier, vol. 133(C).
    30. Lena Dräger & Jan-Oliver Menz & Ulrich Fritsche, 2011. "Perceived Inflation under Loss Aversion," Macroeconomics and Finance Series 201105, University of Hamburg, Department of Socioeconomics.
    31. Fouquau, Julien & Spieser, Philippe K., 2015. "Statistical evidence about LIBOR manipulation: A “Sherlock Holmes” investigation," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 632-643.
    32. Majid Moayyed & Mehdi Shiva, 2023. "The impact of oil price changes on industrial production: a panel smooth-transition approach on G7 countries," International Economics and Economic Policy, Springer, vol. 20(4), pages 595-612, October.
    33. Jude C. Eggoh & Patrick Villieu, 2013. "Un réexamen de la non-linéarité entre le développement financier et la croissance économique," Revue d'économie politique, Dalloz, vol. 123(2), pages 211-236.
    34. Nicholas Apergis & Arusha Cooray, 2017. "Economic Freedom and Income Inequality: Evidence from a Panel of Global Economies— A Linear and a Non-Linear Long-Run Analysis," Manchester School, University of Manchester, vol. 85(1), pages 88-105, January.
    35. Wafa Ghardallou, 2022. "Financial System Development and Democracy: a Panel Smooth Transition Regression Approach for Developing Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(2), pages 1714-1735, June.
    36. Hermann D. Yohou, 2023. "Corruption, tax reform and fiscal space in emerging and developing economies," The World Economy, Wiley Blackwell, vol. 46(4), pages 1082-1118, April.
    37. López-Villavicencio, Antonia & Mignon, Valérie, 2011. "On the impact of inflation on output growth: Does the level of inflation matter?," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 455-464, September.
    38. Mahmut Zortuk & Sinan Çeken, 2016. "Testing Environmental Kuznets Curve in the Selected Transition Economies with Panel Smooth Transition Regression Analysis," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 18(43), pages 537-537, August.
    39. António Afonso & João Tovar Jalles, 2019. "Fiscal Rules and Government Financing Costs," Fiscal Studies, John Wiley & Sons, vol. 40(1), pages 71-90, March.
    40. Dennis Fok & Philip Hans Franses, 2013. "Testing earnings management," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(3), pages 281-292, August.
    41. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 785-794.
    42. Matsuoka,Hideaki, 2020. "Debt Intolerance : Threshold Level and Composition," Policy Research Working Paper Series 9276, The World Bank.
    43. Saia, Artjom, 2023. "Digitalization and CO2 emissions: Dynamics under R&D and technology innovation regimes," Technology in Society, Elsevier, vol. 74(C).
    44. Gabriella Deborah Legrenzi & Costas Milas, 2011. "Debt Sustainability and Financial Crises: Evidence from the GIIPS," CESifo Working Paper Series 3594, CESifo.
    45. Djedje Hermann Yohou & Michaël Goujon & Bertrand Laporte & Samuel Guérineau, 2016. "Is Aid Unfriendly to Tax? African Evidence of Heterogeneous Direct and Indirect Effects," Working Papers halshs-01321620, HAL.
    46. Giulio Cainelli & Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "Spatial agglomeration and productivity in Italy: a panel smooth transition regression approach," Openloc Working Papers 1204, Public policies and local development.
    47. Mustapha JOBARTEH & Huseyin KAYA, 2019. "Non-linear finance-growth nexus for African countries: A panel smooth transition regression approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(620), A), pages 205-222, Autumn.
    48. Davide Furceri & Mr. Prakash Loungani, 2015. "Capital Account Liberalization and Inequality," IMF Working Papers 2015/243, International Monetary Fund.
    49. Ben Hmiden, Oussama & Tatoutchoup, Didier & Nguimkeu, Pierre & Avelé, Donatien, 2024. "Discrepancy and cross-regional bias in sovereign credit ratings: Analyzing the role of public debt," Economic Modelling, Elsevier, vol. 131(C).
    50. António Afonso & João Jalles, 2017. "Do Fiscal Rules Lower Government Financing Costs?," Working Papers REM 2017/15, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    51. Xiaosheng Li & Xia Yan & Qingxian An & Ke Chen & Zhen Shen, 2016. "The coordination between China’s economic growth and environmental emission from the Environmental Kuznets Curve viewpoint," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 233-252, August.
    52. Sophie Béreau & Antonia Lopez Villavicencio & Valérie Mignon, 2008. "Nonlinear Adjustment of the Real Exchange Rate Towards its Equilibrium Value: a Panel Smooth Transition Error Correction Modelling," Working Papers 2008-23, CEPII research center.
    53. Olivier Damette & Majda Seghir, 2018. "Natural resource curse in oil exporting countries: A nonlinear approach," International Economics, CEPII research center, issue 156, pages 231-246.
    54. Xiaoqing Ye & Xiangjun Wu, 2017. "Estimating three-dimensional nonlinear panel data models with interactive effects," Applied Economics Letters, Taylor & Francis Journals, vol. 24(10), pages 708-712, June.
    55. Zhang, Wenwen & Chiu, Yi-Bin, 2020. "Do country risks influence carbon dioxide emissions? A non-linear perspective," Energy, Elsevier, vol. 206(C).
    56. Muhammad Khan, 2016. "Evidence on the functional form of inflation and output growth variability relationship in European economies," International Economics, CEPII research center, issue 146, pages 1-11.
    57. Jude Eggoh, 2012. "Inflation Effects on Finance-Growth Link: A Panel Smooth Threshold Approach," International Economic Journal, Taylor & Francis Journals, vol. 26(4), pages 711-725, June.
    58. Ketenci, Natalya, 2010. "The Feldstein –Horioka Puzzle and structural breaks: evidence from EU members," MPRA Paper 26010, University Library of Munich, Germany.
    59. Magloire LANHA, 2022. "Les institutions influencent-elles la relation," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 55, pages 5-22.
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    62. Silvia Haan-Rietdijk & John Gottman & Cindy Bergeman & Ellen Hamaker, 2016. "Get Over It! A Multilevel Threshold Autoregressive Model for State-Dependent Affect Regulation," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 217-241, March.
    63. Sylvia Kaufmann, 2008. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: A suggestion with an application to Austrian data," Working Papers 144, Oesterreichische Nationalbank (Austrian Central Bank).
    64. Derek Stimel, 2010. "Choice of Aggregate Demand Proxy and its Affect on Phillips Curve Nonlinearity: U.S. Evidence," Economics Bulletin, AccessEcon, vol. 30(1), pages 543-557.
    65. Tzu-Yi Yang & Chieh Liu & Yu-Tai Yang & Ssu-Han Chen, 2023. "The dynamic effect of trading between China and Taiwan under exchange rate fluctuations," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.
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    67. Duygu Yolcu Karadam & Jülide Yildirim & Nadir Öcal, 2017. "Military expenditure and economic growth in Middle Eastern countries and Turkey: a non-linear panel data approach," Defence and Peace Economics, Taylor & Francis Journals, vol. 28(6), pages 719-730, November.
    68. Chakroun, Mohamed, 2009. "Health care expenditure and GDP: An international panel smooth transition approach," MPRA Paper 14322, University Library of Munich, Germany.

  114. Boswijk, H. Peter & Franses, Philip Hans, 2005. "On the Econometrics of the Bass Diffusion Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 255-268, July.
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    1. Sephton, Peter, 2023. "Threshold cointegration and asymmetries between dividends and earnings news," Finance Research Letters, Elsevier, vol. 58(PB).
    2. Sephton, Peter & Mann, Janelle, 2018. "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, vol. 71(C), pages 273-281.
    3. Xiao, Zhijie & Lima, Luiz Renato Regis de Oliveira, 2006. "Testing covariance stationarity," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 632, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    4. Kilian, L. & Caner, M., 1999. "Size Distortions of Tests of the Null Hypothesis of Stationarity: Evidence and Implications for the PPP Debate," Papers 99-05, Michigan - Center for Research on Economic & Social Theory.
    5. Jorge Andrés Tamayo Castaño, 2012. "Asimetrías en la demanda por trabajo en Colombia: el papel del ciclo económico," Borradores de Economia 9286, Banco de la Republica.
    6. Christopher F Baum & John Barkoulas, 2002. "Dynamics of Intra-EMS Interest Rate Linkages," Computing in Economics and Finance 2002 13, Society for Computational Economics.
    7. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    8. Hassan Belkacem Ghassan & Hassan Rafdan Al-Hajhoj & Faruk Balli, 2019. "Bi-Demographic Changes and Current Account using SVAR Modeling: Evidence from Saudi Economy," Working Papers hal-01742574, HAL.
    9. Paul Alagidede & Theodore Panagiotidis & Xu Zhang, 2011. "Causal relationship between stock prices and exchange rates," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 20(1), pages 67-86.
    10. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    11. Manuel Landajo & María José Presno, 2010. "Stationarity testing under nonlinear models. Some asymptotic results," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 392-405, September.
    12. Nazlioglu, Saban & Karul, Cagin, 2017. "A panel stationarity test with gradual structural shifts: Re-investigate the international commodity price shocks," Economic Modelling, Elsevier, vol. 61(C), pages 181-192.
    13. Jönsson, Kristian, 2006. "Testing Stationarity in Small and Medium-Sized Samples when Disturbances are Serially Correlated," Working Papers 2006:20, Lund University, Department of Economics, revised 09 Nov 2009.
    14. Ahmad Zubaidi Baharumshah & Aliyu Alhaji Jibrilla & Abdalla Sirag & Hamisu Sadi Ali & Ibrahim Muye Muhammad, 2016. "Public Revenue-Expenditure Nexus in South Africa: Are there Asymmetries?," South African Journal of Economics, Economic Society of South Africa, vol. 84(4), pages 520-537, December.
    15. Eduard Baumöhl & Štefan Lyócsa & Tomáš Výrost, 2011. "Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 530-544, December.
    16. Lee, Jin & Lee, Young Im, 2012. "Size improvement of the KPSS test using sieve bootstraps," Economics Letters, Elsevier, vol. 116(3), pages 483-486.
    17. Hassan B. Ghassan & Hassan R. Alhajhoj & Faruk Balli, 2022. "Bi-demographic and current account dynamics using SVAR model: evidence from Saudi Arabia," Economic Change and Restructuring, Springer, vol. 55(3), pages 1327-1363, August.
    18. Jushan Bai & Serena Ng, 2001. "A New Look at Panel Testing of Stationarity and the PPP Hypothesis," Boston College Working Papers in Economics 518, Boston College Department of Economics.
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    20. Ai, Xiaohui & Li, Wenbo V. & Liu, Guoqing, 2012. "Karhunen–Loeve expansions for the detrended Brownian motion," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1235-1241.
    21. Peter Sephton & Janelle Mann, 2015. "Nonlinear attractors and asymmetries between non-life insurance premiums and financial markets," Empirical Economics, Springer, vol. 49(3), pages 783-799, November.
    22. Baumöhl, Eduard & Lyócsa, Štefan, 2012. "Constructing weekly returns based on daily stock market data: A puzzle for empirical research?," MPRA Paper 43431, University Library of Munich, Germany.
    23. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    24. Christidou, Maria & Panagiotidis, Theodore & Sharma, Abhijit, 2013. "On the stationarity of per capita carbon dioxide emissions over a century," Economic Modelling, Elsevier, vol. 33(C), pages 918-925.
    25. Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
    26. Lee Kian Lim & Michael McAleer, 2004. "Convergence and catching up in ASEAN: a comparative analysis," Applied Economics, Taylor & Francis Journals, vol. 36(2), pages 137-153.
    27. Giorgio Canarella & Stephen M Miller, 2017. "Inflation Persistence Before and After Inflation Targeting: A Fractional Integration Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 78-103, January.
    28. George Kapetanios, 2007. "Testing for Strict Stationarity," Working Papers 602, Queen Mary University of London, School of Economics and Finance.
    29. Markus Eberhardt & Francis Teal, 2009. "A Common Factor Approach to Spatial Heterogeneity in Agricultural Productivity Analysis," CSAE Working Paper Series 2009-05, Centre for the Study of African Economies, University of Oxford.
    30. Maria Christidou & Theodore Panagiotidis, 2010. "Purchasing Power Parity and the European Single Currency: Some New Evidence," Koç University-TUSIAD Economic Research Forum Working Papers 1018, Koc University-TUSIAD Economic Research Forum.
    31. Bordo, Michael D. & Duca, John V., 2023. "How the new fed municipal bond facility capped municipal-treasury yield spreads in the Covid-19 recession," Journal of the Japanese and International Economies, Elsevier, vol. 67(C).
    32. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    33. Sephton, Peter S., 2019. "El Niño, La Niña, and a cup of Joe," Energy Economics, Elsevier, vol. 84(C).
    34. Sephton, Peter S., 2022. "Revisiting the inflation-hedging properties of precious metals in Africa," Resources Policy, Elsevier, vol. 77(C).
    35. Vasco J. Gabriel, 2001. "Tests for the Null Hypothesis of Cointegration: a Monte Carlo Comparison," NIPE Working Papers 7/2001, NIPE - Universidade do Minho.
    36. Bart Hobijn & Philip Hans Franses, 2000. "Asymptotically perfect and relative convergence of productivity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 59-81.
    37. Yilmazkuday, Hakan, 2009. "Inflation Targeting and Inflation Convergence within Turkey," MPRA Paper 16770, University Library of Munich, Germany.
    38. Ismail H. GENC & Anil RUPASINGHA, 2009. "Time-series Tests of Stochastic Earnings Convergence across US Nonmetropolitan Counties, 1969-2004," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(2).
    39. P. S. Sephton, 2012. "Breaking deterministics, test size and the efficient Wald test for fractional unit roots," Applied Economics Letters, Taylor & Francis Journals, vol. 19(1), pages 83-85, January.
    40. Corrado, L. & Martin, R. & Weeks, M., 2004. "Identifying and Interpreting Convergence Clusters Across Europe," Cambridge Working Papers in Economics 0414, Faculty of Economics, University of Cambridge.
    41. Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
    42. Jönsson, Kristian, 2006. "Finite-Sample Stability of the KPSS Test," Working Papers 2006:23, Lund University, Department of Economics.
    43. Tamayo Castaño, Jorge Andrés, 2012. "Asimetrías en la demanda por trabajo en Colombia : el papel del ciclo económico," Chapters, in: Arango-Thomas, Luis Eduardo & Hamann-Salcedo, Franz Alonso (ed.), El mercado de trabajo en Colombia : hechos, tendencias e instituciones, chapter 12, pages 487-542, Banco de la Republica de Colombia.
    44. Emma Iglesias & Garry Phillips, 2005. "Analysing one-month Euro-market interest rates by fractionally integrated models," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 95-106.
    45. Vincent Bouvatier, 2006. "Hot money inflows in China: How the people's bank of China took up the challenge," Cahiers de la Maison des Sciences Economiques bla06011, Université Panthéon-Sorbonne (Paris 1).
    46. Dawar Hama Khalid Mohammed & Fatih Külahcı & Ahmad Muhammed, 2021. "Determination of possible responses of Radon-222, magnetic effects, and total electron content to earthquakes on the North Anatolian Fault Zone, Turkiye: an ARIMA and Monte Carlo Simulation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(3), pages 2493-2512, September.
    47. Ferrer-Pérez, H. & Ayuda, M.I. & Aznar, A., 2017. "A comparison of two modified stationarity tests. A Monte Carlo study," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 134(C), pages 28-36.
    48. Yongtao Guan, 2008. "A KPSS Test for Stationarity for Spatial Point Processes," Biometrics, The International Biometric Society, vol. 64(3), pages 800-806, September.
    49. Schröder, Michael & Hüfner, Felix P., 2002. "Exchange rate pass-through to consumer prices: a European perspective," ZEW Discussion Papers 02-20, ZEW - Leibniz Centre for European Economic Research.
    50. Kapetanios, George, 2009. "Testing for strict stationarity in financial variables," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2346-2362, December.
    51. L.A. Gil-Alana, 2003. "Testing the Power of a Generalization of the KPSS-Tests against Fractionally Integrated Hypotheses," Computational Economics, Springer;Society for Computational Economics, vol. 22(1), pages 23-38, August.
    52. Bordo, Michael D. & Duca, John V., 2022. "How new Fed corporate bond programs cushioned the Covid-19 recession," Journal of Banking & Finance, Elsevier, vol. 136(C).
    53. Marco G. Ercolani & Zheng Wei, 2010. "An Empirical Analysis of the Lewis-Ranis-FEi Theory of Dualistic Economic Development for China," Discussion Papers 10-06, Department of Economics, University of Birmingham.
    54. Jamie Emerson, 2023. "Education, employment, and labor force participation in the United States," Economics Bulletin, AccessEcon, vol. 43(3), pages 1377-1388.
    55. Lyócsa, Štefan & Baumöhl, Eduard, 2012. "Testing the covariance stationarity of CEE stocks," MPRA Paper 43432, University Library of Munich, Germany.
    56. Mann, Janelle & Sephton, Peter, 2019. "A (negative) replication of ‘The relationship between energy consumption, energy prices, and economic growth: Time series evidence from Asian developing countries’ (Energy Economics, 2000)," Energy Economics, Elsevier, vol. 82(C), pages 78-84.
    57. Rashid Sbia & Muhammad Shahbaz & Ilhan Ozturk, 2017. "Economic growth, financial development, urbanisation and electricity consumption nexus in UAE," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 30(1), pages 527-549, January.
    58. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    59. Hassan B. Ghassan & Hassan R. Al-Hajhoj & Faruk Balli, 2018. "Bi-Demographic Changes and Current Account using SVAR Modeling," Papers 1803.11161, arXiv.org, revised Mar 2019.
    60. Daiki Maki, 2008. "The Performance of Variance Ratio Unit Root Tests Under Nonlinear Stationary TAR and STAR Processes: Evidence from Monte Carlo Simulations and Applications," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 77-94, February.
    61. Peter Sephton, 2017. "Finite Sample Critical Values of the Generalized KPSS Stationarity Test," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 161-172, June.
    62. Alper Kara & Dilem Yildirim & G. Ipek Tunc, 2023. "Market efficiency in non-renewable resource markets: evidence from stationarity tests with structural changes," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 279-290, June.
    63. Marios Poulos, 2016. "Determining the Stationarity Distance via a Reversible Stochastic Process," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-23, October.
    64. Alper Kara & Dilem Yıldırım & Gül İpek Tunç, 2021. "Market Efficiency In Non-Renewable Resource Markets: Evidence From Stationarity Tests With Structural Changes," ERC Working Papers 2103, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
    65. Koch, Cathérine Tahmee, 2014. "Risky adjustments or adjustments to risks: Decomposing bank leverage," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 242-254.
    66. P. S. Sephton, 2010. "Unit roots and purchasing power parity: another kick at the can," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3439-3453.
    67. Ulrich K. Müller, 2002. "Size and Power of Tests for Stationarity in Highly Autocorrelated Time Series," University of St. Gallen Department of Economics working paper series 2002 2002-26, Department of Economics, University of St. Gallen.
    68. Lüders, Erik & Lüders-Amann, Inge & Schröder, Michael, 2004. "The Power Law and Dividend Yields," ZEW Discussion Papers 04-51, ZEW - Leibniz Centre for European Economic Research.
    69. Lee Kian Lim, 2000. "Convergence and Catching Up in South-East Asia: A Comparative Analysis," Econometric Society World Congress 2000 Contributed Papers 1844, Econometric Society.
    70. Rehim Kılıç & Patrick McCarthy, 2012. "Long-run equilibrium and short-run dynamics between risk exposure and highway safety," Empirical Economics, Springer, vol. 42(3), pages 899-913, June.
    71. Baumöhl, Eduard, 2013. "Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach," MPRA Paper 43834, University Library of Munich, Germany.
    72. Ismail Genc & Jon Miller & Anil Rupasingha, 2011. "Stochastic convergence tests for US regional per capita personal income; some further evidence: a research note," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(2), pages 369-377, April.
    73. Ghassan, Hassan & Alhajhoj, Hassan R. & Balli, Faruk, 2018. "Bi-Demographic Changes and Current Account using SVAR Modeling: Evidence from Saudi Arabia," MPRA Paper 93013, University Library of Munich, Germany, revised 01 Feb 2019.

  116. Vroomen, Bjorn & Hans Franses, Philip & van Nierop, Erjen, 2004. "Modeling consideration sets and brand choice using artificial neural networks," European Journal of Operational Research, Elsevier, vol. 154(1), pages 206-217, April.
    See citations under working paper version above.
  117. Franses, Philip Hans & Paap, Richard & Vroomen, Bjorn, 2004. "Forecasting unemployment using an autoregression with censored latent effects parameters," International Journal of Forecasting, Elsevier, vol. 20(2), pages 255-271.

    Cited by:

    1. Antipin, Jan-Erik & Boumediene, Farid Jimmy & Österholm, Pär, 2013. "On the Usefulness of Constant Gain Least Squares when Forecasting the Unemployment Rate," Working Papers 129, National Institute of Economic Research.
    2. Miquel Clar-Lopez & Jordi López-Tamayo & Raúl Ramos, 2014. "Unemployment forecasts, time varying coefficient models and the Okun’s law in Spanish regions," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 247-262.
    3. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    4. Pincheira, Pablo & Hernández, Ana María, 2019. "Forecasting Unemployment Rates with International Factors," MPRA Paper 97855, University Library of Munich, Germany.
    5. Simionescu Mihaela, 2015. "Kalman Filter or VAR Models to Predict Unemployment Rate in Romania?," Naše gospodarstvo/Our economy, Sciendo, vol. 61(3), pages 3-21, June.
    6. Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
    7. Elena Olmedo, 2014. "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 183-197, February.
    8. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    9. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    10. Chen, Chun-I, 2008. "Application of the novel nonlinear grey Bernoulli model for forecasting unemployment rate," Chaos, Solitons & Fractals, Elsevier, vol. 37(1), pages 278-287.
    11. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.

  118. Clements, Michael P. & Franses, Philip Hans & Swanson, Norman R., 2004. "Forecasting economic and financial time-series with non-linear models," International Journal of Forecasting, Elsevier, vol. 20(2), pages 169-183.
    See citations under working paper version above.
  119. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
    See citations under working paper version above.
  120. Philip Hans Franses, 2004. "Do We Think We Make Better Forecasts Than in the Past? A Survey of Academics," Interfaces, INFORMS, vol. 34(6), pages 466-468, December.

    Cited by:

    1. Diana Sánchez-Partida & Rodolfo Rodríguez-Méndez & José Luis Martínez-Flores & Santiago-Omar Caballero-Morales, 2018. "Implementation of Continuous Flow in the Cabinet Process at the Schneider Electric Plant in Tlaxcala, Mexico," Interfaces, INFORMS, vol. 48(6), pages 566-577, November.
    2. Boulaksil, Y. & Franses, Ph.H.B.F., 2008. "Experts' Stated Behavior," ERIM Report Series Research in Management ERS-2008-001-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Franses, Ph.H.B.F., 2006. "Formalizing judgemental adjustment of model-based forecasts," Econometric Institute Research Papers EI 2006-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  121. Philip Hans Franses, 2004. "Fifty years since Koyck (1954)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 381-387, November.

    Cited by:

    1. Hervet, Guillaume & Guitart, Ivan A., 2022. "Increasing the effectiveness of display social media ads for startups: The role of different claims and executional characteristics," Journal of Business Research, Elsevier, vol. 153(C), pages 467-478.
    2. ten Cate, Arie & Franses, Philip Hans, 2008. "Error-correction modelling in discrete and continuous time," Economics Letters, Elsevier, vol. 101(2), pages 140-141, November.

  122. Philip Hans Franses & Yoshinori Kawasaki, 2004. "Do seasonal unit roots matter for forecasting monthly industrial production?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 77-88.

    Cited by:

    1. Richard Kleijn & Herman K. van Dijk, 2006. "Bayes model averaging of cyclical decompositions in economic time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 191-212, March.
    2. Charles S. Bos & Siem Jan Koopman, 2010. "Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production," Tinbergen Institute Discussion Papers 10-017/4, Tinbergen Institute.
    3. Lemmens, Aurélie & Croux, Christophe & Dekimpe, Marnik G., 2008. "Measuring and testing Granger causality over the spectrum: An application to European production expectation surveys," International Journal of Forecasting, Elsevier, vol. 24(3), pages 414-431.
    4. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    5. Garcia-Ferrer, A. & de Juan, A. & Poncela, P., 2006. "Forecasting traffic accidents using disaggregated data," International Journal of Forecasting, Elsevier, vol. 22(2), pages 203-222.

  123. Frédéric Carsoule & Philip Franses, 2003. "A note on monitoring time-varying parameters in an autoregression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 57(1), pages 51-62, February.

    Cited by:

    1. Achim Zeileis, 2005. "A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 445-466.
    2. David Bock, 2008. "Aspects on the control of false alarms in statistical surveillance and the impact on the return of financial decision systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(2), pages 213-227.
    3. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    4. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    5. Pierre Perron & Eduardo Zorita & Eiji Kurozumi, 2017. "Monitoring Parameter Constancy with Endogenous Regressors," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 791-805, September.

  124. Yoshinori Kawasaki & Philip Hans Franses, 2003. "Detecting seasonal unit roots in a structural time series model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(4), pages 373-387.

    Cited by:

    1. Philip Hans Franses & Yoshinori Kawasaki, 2004. "Do seasonal unit roots matter for forecasting monthly industrial production?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 77-88.

  125. Jeanine Kippers & Erjen van Nierop & Richard Paap & Philip Hans Franses, 2003. "An Empirical Study of Cash Payments," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(4), pages 484-508, November.
    See citations under working paper version above.
  126. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    See citations under working paper version above.
  127. Philip Hans Franses, 2003. "The diffusion of scientific publications: The case of Econometrica, 1987," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(1), pages 29-42, January.
    See citations under working paper version above.
  128. Dick van Dijk & Philip Hans Franses, 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 727-744, December.
    See citations under working paper version above.
  129. Roy Kluitman & Philip Hans Franses, 2002. "Estimating volatility on overlapping returns when returns are autocorrelated," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(3), pages 179-188.

    Cited by:

    1. Stephen Taylor & Ming Fang, 2018. "Unbiased weighted variance and skewness estimators for overlapping returns," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-8, December.

  130. Franses, Philip Hans & de Bruin, Paul, 2002. "On data transformations and evidence of nonlinearity," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 621-632, September.
    See citations under working paper version above.
  131. Siem Jan Koopman & Philip Hans Franses, 2002. "Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(5), pages 509-526, December.
    See citations under working paper version above.
  132. Richard Paap & Philip Hans Franses & Marco Van Der Leij, 2002. "Modelling and forecasting level shifts in absolute returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 601-616.

    Cited by:

    1. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Long-memory dynamics in a SETAR model - Applications to stock markets," Post-Print halshs-00179339, HAL.
    2. Broto, Carmen, 2003. "Unobserved component models with asymmetric conditional variances," DES - Working Papers. Statistics and Econometrics. WS ws032003, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Post-Print halshs-00179285, HAL.
    5. Imene Mootamri & Mohamed Boutahar & Anne Peguin-Feissolle, 2008. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Post-Print halshs-00390134, HAL.
    6. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    7. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
    8. de Pooter, M.D. & van Dijk, D.J.C., 2004. "Testing for changes in volatility in heteroskedastic time series - a further examination," Econometric Institute Research Papers EI 2004-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Mohamed Boutahar & Imene Mootamri & Anne Peguin-Feissolle, 2007. "An exponential FISTAR model applied to the US real effective exchange rate," Working Papers halshs-00353836, HAL.

  133. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    See citations under working paper version above.
  134. Pauline Bod & David Blitz & Philip Hans Franses & Roy Kluitman, 2002. "An unbiased variance estimator for overlapping returns," Applied Financial Economics, Taylor & Francis Journals, vol. 12(3), pages 155-158.

    Cited by:

    1. Roy Kluitman & Philip Hans Franses, 2002. "Estimating volatility on overlapping returns when returns are autocorrelated," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(3), pages 179-188.
    2. Ming‐Chang Wang & Yu‐Jia Ding, 2021. "Does the quarterly accrual anomaly exist in Taiwan's stock market? Evidence from Manager's earnings management," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(3), pages 688-701, April.
    3. Stephen Taylor & Ming Fang, 2018. "Unbiased weighted variance and skewness estimators for overlapping returns," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-8, December.

  135. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    See citations under working paper version above.
  136. Fok, Dennis & Franses, Philip Hans, 2002. "Ordered logit analysis for selectively sampled data," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 477-497, September.
    See citations under working paper version above.
  137. Philip Hans Franses, 2002. "From first submission to citation: an empirical analysis," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(4), pages 496-509, November.
    See citations under working paper version above.
  138. Philip Hans Franses & Michael McAleer, 2002. "Financial volatility: an introduction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 419-424.

    Cited by:

    1. Ling, Shiqing & McAleer, Michael & Tong, Howell, 2015. "Frontiers in Time Series and Financial Econometrics: An overview," Journal of Econometrics, Elsevier, vol. 189(2), pages 245-250.
    2. Caginalp, Carey & Caginalp, Gunduz & Swigon, David, 2021. "Stochastic asset flow equations: Interdependence of trend and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    3. Carey Caginalp & Gunduz Caginalp, 2019. "Derivation of non-classical stochastic price dynamics equations," Papers 1908.01103, arXiv.org, revised Aug 2020.
    4. Junru Zhang & Hadrian Geri Djajadikerta & Zhaoyong Zhang, 2018. "Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    5. Ooms, M., 2008. "Trends in Applied Econometrics Software Development 1985-2008, an analysis of Journal of Applied Econometrics research articles, software reviews, data and code," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    6. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    7. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    8. Ekong, Christopher N. & Onye, Kenneth U., 2017. "Application of Garch Models to Estimate and Predict Financial Volatility of Daily Stock Returns in Nigeria," MPRA Paper 88309, University Library of Munich, Germany.
    9. Ling, S. & McAleer, M.J. & Tong, H., 2015. "Frontiers in Time Series and Financial Econometrics," Econometric Institute Research Papers EI 2015-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Liu, Heping & Erdem, Ergin & Shi, Jing, 2011. "Comprehensive evaluation of ARMA-GARCH(-M) approaches for modeling the mean and volatility of wind speed," Applied Energy, Elsevier, vol. 88(3), pages 724-732, March.
    11. Ipek M. Yurttaguler, 2024. "Analysis of Istanbul Stock Market Returns Volatility with ARCH and GARCH Models," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(74-1), pages 37-58, June.
    12. Caginalp, Carey & Caginalp, Gunduz, 2020. "Derivation of non-classical stochastic price dynamics equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    13. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.

  139. Pelzer, Ben & Eisinga, Rob & Franses, Philip Hans, 2002. "Inferring Transition Probabilities from Repeated Cross Sections," Political Analysis, Cambridge University Press, vol. 10(2), pages 113-133, April.

    Cited by:

    1. Pelzer, B. & Eisinga, R. & Franses, Ph.H.B.F., 2002. "Ecological panel inference in repeated cross sections," Econometric Institute Research Papers EI 2002-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. William Lim & Gaurav Khemka & David Pitt & Bridget Browne, 2019. "A method for calculating the implied no-recovery three-state transition matrix using observable population mortality incidence and disability prevalence rates among the elderly," Journal of Population Research, Springer, vol. 36(3), pages 245-282, September.

  140. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.

    Cited by:

    1. Cheng, Ka Ming, 2022. "Doubts on natural rate of unemployment: Evidence and policy implications," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 230-239.
    2. Kapetanios, George, 2006. "Nonlinear autoregressive models and long memory," Economics Letters, Elsevier, vol. 91(3), pages 360-368, June.
    3. Baillie, Richard T. & Kapetanios, George, 2007. "Testing for Neglected Nonlinearity in Long-Memory Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 447-461, October.
    4. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2004. "Non-Linearities And Fractional Integration In The Us Unemployment Rate," Public Policy Discussion Papers 04-17, Economics and Finance Section, School of Social Sciences, Brunel University.
    5. Anne Peguin-Feissolle & Gilles Dufrénot & Dominique Guegan, 2006. "Changing-regime volatility : A fractionally integrated SETAR model," Working Papers halshs-00410540, HAL.
    6. James D. Hamilton, 2005. "What's Real About the Business Cycle?," NBER Working Papers 11161, National Bureau of Economic Research, Inc.
    7. Scharth, Marcel & Medeiros, Marcelo C., 2009. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
    8. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
    10. Thomaidis, Nikolaos S. & Biskas, Pandelis N., 2021. "Fundamental pricing laws and long memory effects in the day-ahead power market," Energy Economics, Elsevier, vol. 100(C).
    11. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Long-memory dynamics in a SETAR model - Applications to stock markets," Post-Print halshs-00179339, HAL.
    12. Kurt Graden Lunsford, 2023. "Business Cycles and Low-Frequency Fluctuations in the US Unemployment Rate," Working Papers 23-19, Federal Reserve Bank of Cleveland.
    13. David Ubilava, 2014. "El Niño Southern Oscillation and the fishmeal–soya bean meal price ratio: regime-dependent dynamics revisited," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(4), pages 583-604.
    14. Baillie, Richard T. & Kapetanios, George & Papailias, Fotis, 2014. "Bandwidth selection by cross-validation for forecasting long memory financial time series," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 129-143.
    15. Smallwood Aaron D, 2005. "Joint Tests for Non-linearity and Long Memory: The Case of Purchasing Power Parity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-30, June.
    16. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2018. "A simple test on structural change in long-memory time series," Economics Letters, Elsevier, vol. 163(C), pages 90-94.
    17. Ivan D. Trofimov, 2024. "A Time Series Analysis of Corporate Profit Rates in Selected Developed Economies: Asymmetries, Non-linearity and Mean Reversion," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(2), pages 303-338, June.
    18. Aaron D. Smallwood, 2016. "A Monte Carlo Investigation of Unit Root Tests and Long Memory in Detecting Mean Reversion in I(0) Regime Switching, Structural Break, and Nonlinear Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 986-1012, June.
    19. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    20. José M. Belbute & Alfredo Marvão Pereira, 2015. "Does Final Energy Demand in Portugal Exhibit Long Memory? A Fractional Integration Analysis," Working Papers 163, Department of Economics, College of William and Mary.
    21. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2008. "Modelling the US, UK and Japanese unemployment rates: Fractional integration and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4998-5013, July.
    22. Cevik, Emrah Ismail & Dibooglu, Sel, 2013. "Persistence and non-linearity in US unemployment: A regime-switching approach," Economic Systems, Elsevier, vol. 37(1), pages 61-68.
    23. Baillie, Richard T. & Kapetanios, George, 2008. "Nonlinear models for strongly dependent processes with financial applications," Journal of Econometrics, Elsevier, vol. 147(1), pages 60-71, November.
    24. T. Panagiotidis & G. Pelloni, 2004. "Non-Linearity in the Canadian and US Labour Markets: Univariate and Multivariate Evidence from A Battery of Tests," Working Papers 506, Dipartimento Scienze Economiche, Universita' di Bologna.
    25. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2020. "Are unemployment rates in OECD countries stationary? Evidence from univariate and panel unit root tests," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    26. Amine LAHIANI & Olivier SCAILLET, 2008. "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," Swiss Finance Institute Research Paper Series 08-42, Swiss Finance Institute.
    27. David Ubilava & Matt Holt, 2013. "El Niño southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 273-297, April.
    28. Lean, Hooi Hooi & Smyth, Russell, 2009. "Long memory in US disaggregated petroleum consumption: Evidence from univariate and multivariate LM tests for fractional integration," Energy Policy, Elsevier, vol. 37(8), pages 3205-3211, August.
    29. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Post-Print halshs-00179285, HAL.
    30. Nasr, Adnen Ben & Balcilar, Mehmet & Ajmi, Ahdi N. & Aye, Goodness C. & Gupta, Rangan & van Eyden, Reneé, 2015. "Causality between inflation and inflation uncertainty in South Africa: Evidence from a Markov-switching vector autoregressive model," Emerging Markets Review, Elsevier, vol. 24(C), pages 46-68.
    31. Dipak Ghosh & Swarna (Bashu) Dutt, . "Nonstationarity and Nonlinearity in the US Unemployment Rate: A Re-examination," Journal for Economic Educators, Middle Tennessee State University, Business and Economic Research Center.
    32. Elena Olmedo, 2014. "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 183-197, February.
    33. Christian Peretti, 2007. "Long Memory and Hysteresis," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 363-389, Springer.
    34. Hyung, N. & Franses, Ph.H.B.F., 2002. "Inflation rates; long-memoray, level shifts, or both?," Econometric Institute Research Papers EI 2002-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    35. Marianne Sensier & Denise R. Osborn & Nadir Öcal, 2002. "Asymmetric Interest Rate Effects for the UK Real Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 315-339, September.
    36. Ralf Becker & Denise Osborn, 2007. "Weighted smooth transition regressions," Economics Discussion Paper Series 0724, Economics, The University of Manchester.
    37. Eric Hillebrand & Marcelo C. Medeiros, 2016. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 23-41, January.
    38. Mohamed El Hedi Arouri & Shawkat Hammoudeh & Amine Lahiani & Duc Khuong Nguyen, 2013. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," Working Papers hal-00798033, HAL.
    39. Coakley, Jerry & Fuertes, Ana-Maria, 2006. "Testing for sign and amplitude asymmetries using threshold autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 30(4), pages 623-654, April.
    40. Patrick J. Wilson & L.J. Perry, 2004. "Forecasting Australian Unemployment Rates using Spectral Analysis," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 7(4), pages 459-480, December.
    41. Imene Mootamri & Mohamed Boutahar & Anne Peguin-Feissolle, 2008. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Post-Print halshs-00390134, HAL.
    42. Philip Hans Franses & Namwon Hyung, 2005. "Forecasting time series with long memory and level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 1-16.
    43. Yaya, OlaOluwa S & Ogbonna, Ephraim A & Furuoka, Fumitaka & Gil-Alana, Luis A., 2019. "A new unit root analysis for testing hysteresis in unemployment," MPRA Paper 96621, University Library of Munich, Germany.
    44. Asano, Takao & Yokoo, Masanori, 2019. "Chaotic dynamics of a piecewise linear model of credit cycles," Journal of Mathematical Economics, Elsevier, vol. 80(C), pages 9-21.
    45. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    46. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    47. Dalla, Violetta & Giraitis, Liudas & Robinson, Peter M., 2020. "Asymptotic theory for time series with changing mean and variance," Journal of Econometrics, Elsevier, vol. 219(2), pages 281-313.
    48. Gilles Dufrenot & Elisabeth Grimaud & Eugénie Latil & Valerie Mignon, 2008. "Modelling The Slow Mean‐Reversion Of The Central And Eastern European Countries' Real Exchange Rates," Manchester School, University of Manchester, vol. 76(1), pages 21-43, January.
    49. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    50. Moosa, Imad A. & Ma, Ming, 2018. "Linear and Nonlinear Attractors in Purchasing Power Parity," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 149-172.
    51. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    52. Yaya, OlaOluwa Simon & Gil-Alana, Luis Alberiko & Carcel, Hector, 2015. "Testing fractional persistence and non-linearities in the natural gas market: An application of non-linear deterministic terms based on Chebyshev polynomials in time," Energy Economics, Elsevier, vol. 52(PA), pages 240-245.
    53. Mohamed Boutahar & Imene Mootamri & Anne Peguin-Feissolle, 2007. "An exponential FISTAR model applied to the US real effective exchange rate," Working Papers halshs-00353836, HAL.
    54. G. Dufrenot & E. Grimaud & E. Latil & V. Mignon, 2003. "Real exchange rate misalignment in Hungary: a fractionally integrated threshold model," THEMA Working Papers 2003-07, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    55. Vijverberg, Chu-Ping C., 2009. "A time deformation model and its time-varying autocorrelation: An application to US unemployment data," International Journal of Forecasting, Elsevier, vol. 25(1), pages 128-145.
    56. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2013. "Asymmetric and Time-Varying Causality between Inflation and Inflation Uncertainty in G-7 Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 60(1), pages 1-42, February.
    57. Gilles DUFRENOT & Elisabeth GRIMAUD & Eug=E9nie LATIL & Val=E9rie MIGNON, 2003. "Real exhange rate misalignment in Hungary: a fractionally integrated=20 threshold model," Econometrics 0309001, University Library of Munich, Germany.
    58. Gross, Marco & Binder, Michael, 2013. "Regime-switching global vector autoregressive models," Working Paper Series 1569, European Central Bank.
    59. Richard T. Baillie & George Kapetanios, 2006. "Nonlinear Models with Strongly Dependent Processes and Applications to Forward Premia and Real Exchange Rates," Working Papers 570, Queen Mary University of London, School of Economics and Finance.
    60. Lena Vogel & Jan-Oliver Menz & Ulrich Fritsche, 2009. "Prospect Theory and Inflation Perceptions - An Empirical Assessment," Macroeconomics and Finance Series 200903, University of Hamburg, Department of Socioeconomics.
    61. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.

  141. Franses, Philip Hans & Teräsvirta, Timo, 2001. "Introduction To The Special Issue: Nonlinear Modeling Of Multivariate Macroeconomic Relations," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 461-465, September.

    Cited by:

    1. Donayre, Luiggi, 2014. "Estimated Thresholds In The Response Of Output To Monetary Policy: Are Large Policy Changes Less Effective?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(1), pages 41-64, January.

  142. Philip Hans Franses, 2001. "How to deal with intercept and trend in practical cointegration analysis?," Applied Economics, Taylor & Francis Journals, vol. 33(5), pages 577-579.
    See citations under working paper version above.
  143. Philip Hans Franses, 2001. "Some comments on seasonal adjustment," Revista de Economía del Rosario, Universidad del Rosario, June.

    Cited by:

    1. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    2. Carlos A. Medel V. & Michael Pedersen, 2010. "Incertidumbre en las Series Desestacionalizadas de Actividad y Demanda en Chile," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 13(1), pages 63-72, April.

  144. Ben Pelzer & Rob Eisinga & Philip Hans Franses, 2001. "Estimating Transition Probabilities from a Time Series of Independent Cross Sections," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 55(2), pages 249-262, July.

    Cited by:

    1. Boualem Rabta & Bart van den Boom & Vasco Molini, 2016. "A Continuous†time Markov Chain Approach for Modeling of Poverty Dynamics: Application to Mozambique," African Development Review, African Development Bank, vol. 28(4), pages 482-495, December.
    2. Arie ten Cate, 2014. "Maximum likelihood estimation of the Markov chain model with macro data and the ecological inference model," CPB Discussion Paper 284, CPB Netherlands Bureau for Economic Policy Analysis.
    3. José Carlos Ramírez & Francisco Ortiz-Arango & Leovardo Mata, 2021. "The Markovian Pattern of Social Deprivation for Mexicans with Diabetes," Mathematics, MDPI, vol. 9(7), pages 1-17, April.

  145. Lof, Marten & Hans Franses, Philip, 2001. "On forecasting cointegrated seasonal time series," International Journal of Forecasting, Elsevier, vol. 17(4), pages 607-621.
    See citations under working paper version above.
  146. Hobijn, Bart & Franses, Philip Hans, 2001. "Are living standards converging?," Structural Change and Economic Dynamics, Elsevier, vol. 12(2), pages 171-200, July.

    Cited by:

    1. Jhonny Moncada & David Hincapié Vélez, 2013. "Convergencia en calidad de vida en Medellín 2004-2011. Un análisis espacial no paramétrico," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 31(70), pages 268-314, July.
    2. Rubiane Daniele Cardoso Almeida & Philipp Ehrl & Tito Belchior Silva Moreira, 2021. "Social and Economic Convergence Across Brazilian States Between 1990 and 2010," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(1), pages 225-246, August.
    3. Eric Neumayer, 2004. "HIV/AIDS and its impact on convergence in life expectancy, infant and child survival rates," HEW 0405001, University Library of Munich, Germany.
    4. Maria Cracolici & Miranda Cuffaro & Peter Nijkamp, 2010. "The Measurement of Economic, Social and Environmental Performance of Countries: A Novel Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 95(2), pages 339-356, January.
    5. David Canning, 2010. "Progress in Health around the World," Human Development Research Papers (2009 to present) HDRP-2010-43, Human Development Report Office (HDRO), United Nations Development Programme (UNDP).
    6. Gordon Anderson, Alessio Farcomeni, Maria Grazia Pittau and Roberto Zelli, 2019. "Multidimensional Nation Wellbeing, More Equal yet More Polarized: An Analysis of the Progress of Human Development Since 1990," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(1), pages 1-22, March.
    7. Kshamanidhi Adabar, 2004. "Convergence of Standards of Living Across Indian States," Working Papers 153, Institute for Social and Economic Change, Bangalore.
    8. Sandy Dall'erba & Julie Le Gallo, 2008. "Regional convergence and the impact of European structural funds over 1989–1999: A spatial econometric analysis," Papers in Regional Science, Wiley Blackwell, vol. 87(2), pages 219-244, June.
    9. M. Niaz Asadullah & Antonio Savoia, 2017. "Poverty reduction during 1990-2013: Did Millennium Development Goals adoption and state capacity matter?," Global Development Institute Working Paper Series esid-093-17, GDI, The University of Manchester.
    10. G. Madonia & M. Cracolici & M. Cuffaro, 2013. "Exploring Wider Well-Being in the EU-15 Countries: An Empirical Application of the Stiglitz Report," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 111(1), pages 117-140, March.
    11. Simplice A, Asongu, 2012. "African Development: Beyond Income Convergence," MPRA Paper 36054, University Library of Munich, Germany.
    12. Adolfo Meisel Roca & Angela Granger S, 2019. "¿Atrapados en la periferia? Brechas de calidad en la educación en Colombia: Pruebas Saber 11 (2000-2018)," Documentos Departamento de Economía 18078, Universidad del Norte.
    13. DECANCK, Koen & DECOSTER, André & SCHOOKAERT, Erik, 2009. "The evolution of world inequality in well-being," LIDAM Reprints CORE 2140, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Duncan, Roberto & Toledo, Patricia, 2018. "Long-run overweight levels and convergence in body mass index," Economics & Human Biology, Elsevier, vol. 31(C), pages 26-39.
    15. Bienvenido Ortega & Antonio Casquero & Jesús Sanjuán, 2016. "Corruption and Convergence in Human Development: Evidence from 69 Countries During 1990–2012," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(2), pages 691-719, June.
    16. Sulekha Hembram & Sohini Mukherjee & Sushil Kr. Haldar, 2020. "Regional convergence of social and economic development in the districts of West Bengal, India: Do clubs exist? Does space matter? An empirical analysis using DLHS I–IV and NFHS IV data," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 22(1), pages 58-90, June.
    17. Maria Francesca Cracolici & Miranda Cuffaro & Peter Nijkamp, 2008. "Analysis of Spatial Disparities by a Structural Equations Model," Tinbergen Institute Discussion Papers 08-058/3, Tinbergen Institute.
    18. Cuffaro , Miranda & Cracolici, Maria Francesca & Nijkamp, Peter, 2006. "Economic convergence vs. socio-economic convergence in space," Serie Research Memoranda 0020, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    19. Cracolici, Maria Francesca & Cuffaro, Miranda & Lacagnina, Valerio, 2018. "Assessment of Sustainable Well-being in the Italian Regions: An Activity Analysis Model," Ecological Economics, Elsevier, vol. 143(C), pages 105-110.
    20. Vijay K. Mathur & Sheldon H. Stein, 2005. "Do amenities matter in attracting knowledge workers for regional economic development?," Papers in Regional Science, Wiley Blackwell, vol. 84(2), pages 251-269, June.
    21. ArdIc, Oya PInar, 2006. "The gap between the rich and the poor: Patterns of heterogeneity in the cross-country data," Economic Modelling, Elsevier, vol. 23(3), pages 538-555, May.
    22. Saadet Kasman & Adnan Kasman, 2021. "Convergence in obesity and overweight rates across OECD countries: evidence from the stochastic and club convergence tests," Empirical Economics, Springer, vol. 61(2), pages 1063-1096, August.
    23. Neumayer, Eric, 2003. "Beyond income: convergence in living standards, big time," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 275-296, September.
    24. Diego Comin & Bart Hobijn & Emilie Rovito, 2006. "Five Facts You Need to Know About Technology Diffusion," NBER Working Papers 11928, National Bureau of Economic Research, Inc.
    25. Christopher GRIGORIOU, 2008. "Survival Convergence: Specification Matters," Working Papers 200815, CERDI.
    26. Ángeles Sánchez & Jorge Chica-Olmo & Juan de Dios Jiménez-Aguilera, 2018. "A Space–Time Study for Mapping Quality of Life in Andalusia During the Crisis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(2), pages 699-728, January.
    27. Seyithan Ahmet Ates & Kursad Derinkuyu, 2021. "Green growth and OECD countries: measurement of country performances through distance-based analysis (DBA)," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 15062-15073, October.
    28. Binelli, Chiara & Loveless, Matthew & Whitefield, Stephen, 2015. "What Is Social Inequality and Why Does it Matter? Evidence from Central and Eastern Europe," World Development, Elsevier, vol. 70(C), pages 239-248.
    29. Vicente Royuela & Manuel Artis, 2006. "Convergence analysis in terms of quality of life in the urban systems of the Barcelona province, 1991-2000," Regional Studies, Taylor & Francis Journals, vol. 40(5), pages 485-492.
    30. Miranda Cuffaro & Maria Francesca Cracolici & Peter Nijkamp, 2008. "Measuring the Performance of Italian Regions on Social and Economic Dimensions," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2008(1), pages 5-25.
    31. Suman Seth & Gaston Yalonetzky, 2016. "Has the world converged? A robust analysis of non-monetary bounded indicators," Working Papers 398, ECINEQ, Society for the Study of Economic Inequality.
    32. Christopher GRIGORIOU & Patrick GUILLAUMONT, 2004. "Child Mortality under Chinese Reforms," Working Papers 200410, CERDI.
    33. Weber, Axel A. & Beck, Günter W., 2005. "Price stability, inflation convergence and diversity in EMU: Does one size fit all?," CFS Working Paper Series 2005/30, Center for Financial Studies (CFS).
    34. Giles, David E.A. & Feng, Hui, 2005. "Output and well-being in industrialized nations in the second half of the 20th century: testing for convergence using fuzzy clustering analysis," Structural Change and Economic Dynamics, Elsevier, vol. 16(2), pages 285-308, June.
    35. Matthew Cole & Eric Neumayer, 2003. "The pitfalls of convergence analysis: is the income gap really widening?," Applied Economics Letters, Taylor & Francis Journals, vol. 10(6), pages 355-357.
    36. Andres Marchante & Bienvenido Ortega, 2006. "Quality of life and economic convergence across Spanish regions, 1980-2001," Regional Studies, Taylor & Francis Journals, vol. 40(5), pages 471-483.
    37. Duncan, Roberto & Toledo, Patricia, 2018. "Do overweight and obesity prevalence rates converge in Europe?," Research in Economics, Elsevier, vol. 72(4), pages 482-493.
    38. Welsch, Heinz & Bonn, Udo, 2008. "Economic convergence and life satisfaction in the European Union," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(3), pages 1153-1167, June.
    39. M. Happich & T. von Lengerke, 2007. "Convergence of life expectancy in the European Union: a Markov approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 175-178.
    40. Sulekha Hembram & Sushil Kr. Haldar, 2020. "Is India experiencing health convergence? An empirical analysis," Economic Change and Restructuring, Springer, vol. 53(4), pages 591-618, November.
    41. Maliranta, Mika, . "Micro Level Dynamics of Productivity Growth. An Empirical Analysis of the Great Leap in Finnish Manufacturing Productivity in 1975-2000," ETLA A, The Research Institute of the Finnish Economy, number 38, June.
    42. Weber, Axel A. & Beck, Günter W., 2005. "Inflation rate dispersion and convergence in monetary and economic unions: lessons for the ECB," CFS Working Paper Series 2005/31, Center for Financial Studies (CFS).
    43. David E.A. Giles & Hui Feng, 2003. "Testing For Convergence in Output and in 'Well-Being' in Industrialized Countries," Econometrics Working Papers 0302, Department of Economics, University of Victoria.
    44. Duncan, Roberto & Toledo, Patricia, 2019. "Inequality in body mass indices across countries: Evidence from convergence tests," Economics & Human Biology, Elsevier, vol. 33(C), pages 40-57.

  147. Fok, Dennis & Franses, Philip Hans, 2001. "Forecasting market shares from models for sales," International Journal of Forecasting, Elsevier, vol. 17(1), pages 121-128.
    See citations under working paper version above.
  148. Taylor, Nick & Dijk, Dick van & Franses, Philip Hans & Lucas, Andre, 2000. "SETS, arbitrage activity, and stock price dynamics," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1289-1306, August.
    See citations under working paper version above.
  149. Franses Philip Hans & de Bruin Paul, 2000. "Seasonal Adjustment and the Business Cycle in Unemployment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(2), pages 1-14, July.
    See citations under working paper version above.
  150. Arino, Miguel A. & Franses, Philip Hans, 2000. "Forecasting the levels of vector autoregressive log-transformed time series," International Journal of Forecasting, Elsevier, vol. 16(1), pages 111-116.
    See citations under working paper version above.
  151. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.

    Cited by:

    1. Richard T. Carson & Derrick H. Sun & Yixiao Sun, 2024. "Random Utility Models with Skewed Random Components: the Smallest versus Largest Extreme Value Distribution," Papers 2405.08222, arXiv.org, revised May 2024.
    2. Xiaokun Wang & Kara M. Kockelman, 2009. "Baysian Inference For Ordered Response Data With A Dynamic Spatial‐Ordered Probit Model," Journal of Regional Science, Wiley Blackwell, vol. 49(5), pages 877-913, December.
    3. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    4. Zdenka MALÁ & Michal MALÝ, 2013. "The determinants of adopting organic farming practices: a case study in the Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 59(1), pages 19-28.
    5. van Heerde, H.J. & Helsen, K. & Dekimpe, M.G., 2005. "Managing Product-Harm Crises," ERIM Report Series Research in Management ERS-2005-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2003. "Modeling Dynamic Effects of the Marketing Mix on Market Shares," ERIM Report Series Research in Management ERS-2003-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Lilach Nachum & Srilata Zaheer & Shulamith Gross, 2008. "Does It Matter Where Countries Are? Proximity to Knowledge, Markets and Resources, and MNE Location Choices," Management Science, INFORMS, vol. 54(7), pages 1252-1265, July.
    8. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
    9. Fok, Dennis & Paap, Richard & Franses, Philip Hans, 2012. "Modeling dynamic effects of promotion on interpurchase times," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3055-3069.
    10. Meng, Ting & Klepacka, Anna M. & Florkowski, Wojciech J. & Braman, Kristine, 2015. "What drives an environmental horticultural firm to start recycling plastics? Results of a Georgia survey," Resources, Conservation & Recycling, Elsevier, vol. 102(C), pages 1-8.
    11. Alan L. Montgomery & Shibo Li & Kannan Srinivasan & John C. Liechty, 2004. "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, INFORMS, vol. 23(4), pages 579-595, November.
    12. Fok, D. & Horváth, C. & Paap, R. & Franses, Ph.H.B.F., 2004. "A hierarchical Bayes error correction model to explain dynamic effects," Econometric Institute Research Papers EI 2004-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Choudhury, Charisma F. & Yang, Lang & de Abreu e Silva, João & Ben-Akiva, Moshe, 2018. "Modelling preferences for smart modes and services: A case study in Lisbon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 15-31.
    14. Song, Lianlian & Shi, Yang & Tso, Geoffrey Kwok Fai & Lo, Hing Po, 2021. "Forecasting week-to-week television ratings using reduced-form and structural dynamic models," International Journal of Forecasting, Elsevier, vol. 37(1), pages 302-321.
    15. John C. Liechty & Duncan K. H. Fong & Wayne S. DeSarbo, 2005. "Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(2), pages 285-293, November.
    16. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2019. "Inference on Semiparametric Multinomial Response Models," Boston College Working Papers in Economics 980, Boston College Department of Economics.
    17. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2001. "Econometric Analysis of the Market Share Attraction Model," ERIM Report Series Research in Management ERS-2001-25-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Business and Economics.
    19. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2020. "Inference on Semiparametric Multinomial Response Models," Discussion Papers Series 627, School of Economics, University of Queensland, Australia.
    20. Can, Vo Van, 2013. "Estimation of travel mode choice for domestic tourists to Nha Trang using the multinomial probit model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 149-159.
    21. Martijn G. de Jong & Donald R. Lehmann & Oded Netzer, 2012. "State-Dependence Effects in Surveys," Marketing Science, INFORMS, vol. 31(5), pages 838-854, September.
    22. M. Tolga Akçura & Füsun F. Gönül & Elina Petrova, 2004. "Consumer Learning and Brand Valuation: An Application on Over-the-Counter Drugs," Marketing Science, INFORMS, vol. 23(1), pages 156-169, April.
    23. Korkmaz, E. & Fok, D. & Kuik, R., 2014. "The Need for Market Segmentation in Buy-Till-You-Defect Models," ERIM Report Series Research in Management ERS-2014-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    24. Harald Van Heerde & Kristiaan Helsen & Marnik G. Dekimpe, 2007. "The Impact of a Product-Harm Crisis on Marketing Effectiveness," Marketing Science, INFORMS, vol. 26(2), pages 230-245, 03-04.

  152. Philip Hans Franses And A. M. Robert Taylor, 2000. "Determining the order of differencing in seasonal time series processes," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 250-264.
    See citations under working paper version above.
  153. Groenen, Patrick J. F. & Franses, Philip Hans, 2000. "Visualizing time-varying correlations across stock markets," Journal of Empirical Finance, Elsevier, vol. 7(2), pages 155-172, August.

    Cited by:

    1. Chun-Xiao Nie, 2021. "Studying the correlation structure based on market geometry," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 411-441, April.
    2. Andrea Beltratti & Claudio Morana, 2006. "Comovements in International Stock Markets," ICER Working Papers 3-2006, ICER - International Centre for Economic Research.
    3. Lehkonen, Heikki & Heimonen, Kari, 2014. "Timescale-dependent stock market comovement: BRICs vs. developed markets," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 90-103.
    4. Carrizosa, Emilio & Guerrero, Vanesa & Romero Morales, Dolores, 2019. "Visualization of complex dynamic datasets by means of mathematical optimization," Omega, Elsevier, vol. 86(C), pages 125-136.
    5. Claudio Morana, 2006. "International Stock Markets Comovements: the Role of Economic and Financial Integration," ICER Working Papers 25-2006, ICER - International Centre for Economic Research.
    6. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    7. N Blasco & P Corredor & S Ferreruela, 2011. "Detecting intentional herding: what lies beneath intraday data in the Spanish stock market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1056-1066, June.
    8. Giampaolo Gabbi, 2005. "Semi-correlations as a tool for geographical and sector asset allocation," The European Journal of Finance, Taylor & Francis Journals, vol. 11(3), pages 271-281.
    9. Dirk Brounen & Maarten Jennen, 2009. "Asymmetric Properties of Office Rent Adjustment," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 336-358, October.
    10. Ji, Aiwen & Shang, Pengjian, 2019. "Analysis of financial time series through forbidden patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    11. Bera, Anil K. & Kim, Sangwhan, 2002. "Testing constancy of correlation and other specifications of the BGARCH model with an application to international equity returns," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 171-195, March.
    12. Miroslav Plasil & Ivana Kubicova, 2012. "Contingent Claims Analysis And The Inter-Sector Transmission Of Credit Risk," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2011/2012, chapter 0, pages 129-139, Czech National Bank.

  154. Bart Hobijn & Philip Hans Franses, 2000. "Asymptotically perfect and relative convergence of productivity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 59-81.

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    1. Guglielmo Maria Caporale & Burcu Erdogan & Vladimir Kuzin, 2009. "Testing for Convergence in Stock Markets: A Non-Linear Factor Approach," CESifo Working Paper Series 2845, CESifo.
    2. Vogelsang, Timothy J. & Franses, Philip Hans, 2001. "Testing for Common Deterministic Trend Slopes," Working Papers 01-15, Cornell University, Center for Analytic Economics.
    3. Lau, Chi Keung & Pal, Shreya & Mahalik, Mantu Kumar & Gozgor, Giray, 2022. "Economic globalization convergence in high and low globalized developing economies: Implications for the post Covid-19 era," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 1027-1039.
    4. Breandán Ó'hUallacháin, 2008. "Regional growth transition clubs in the United States," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 33-53, March.
    5. Ozgen Sayginsoy, 2004. "Powerful and Serial Correlation Robust Tests of the Economic Convergence Hypothesis," Discussion Papers 04-07, University at Albany, SUNY, Department of Economics.
    6. Capolupo, Rosa, 2009. "The New Growth Theories and Their Empirics after Twenty Years," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-72.
    7. Hashem Pesaran, M., 2007. "A pair-wise approach to testing for output and growth convergence," Journal of Econometrics, Elsevier, vol. 138(1), pages 312-355, May.
    8. Manfred M. Fischer & James P. LeSage, 2012. "A Bayesian approach to identifying and interpreting regional convergence clubs in Europe," ERSA conference papers ersa12p217, European Regional Science Association.
    9. Silva Lopes, Artur C., 2021. "Most likely you go your way (and I'll go mine): non-convergent incomes with a new DF-Fourier test," MPRA Paper 107676, University Library of Munich, Germany, revised 19 Mar 2021.
    10. Steven N. Durlauf & Andros Kourtellos & Chih Ming Tan, 2008. "Empirics of Growth and Development," Chapters, in: Amitava Krishna Dutt & Jaime Ros (ed.), International Handbook of Development Economics, Volumes 1 & 2, volume 0, chapter 3, Edward Elgar Publishing.
    11. Johnson, Paul & Papageorgiou, Chris, 2018. "What Remains of Cross-Country Convergence?," MPRA Paper 89355, University Library of Munich, Germany.
    12. Marina Glushenkova & Andros Kourtellos & Marios Zachariadis, 2016. "Barriers to price convergence," University of Cyprus Working Papers in Economics 02-2016, University of Cyprus Department of Economics.
    13. Mateusz Tomal, 2024. "A new time-varying method for club convergence analysis," Economics and Business Letters, Oviedo University Press, vol. 13(4), pages 194-202.
    14. Matsuki, Takashi & Usami, Ryoichi, 2007. "China's Regional Convergence in Panels with Multiple Structural Breaks," MPRA Paper 10167, University Library of Munich, Germany, revised 17 May 2008.
    15. Thanasis Stengos & Ege Yazgan & Harun Ozkan, 2016. "Persistence in Convergence: Some further results," Working Papers 1605, University of Guelph, Department of Economics and Finance.
    16. Garcia-Hiernaux, Alfredo & Guerrero, David E., 2021. "Price convergence: Representation and testing," Economic Modelling, Elsevier, vol. 104(C).
    17. Vasco M.Carvalho & Andrew C.Harvey, 2002. "Growth, Cycles and Convergence in US Regional Time Series," Cambridge Working Papers in Economics 0221, Faculty of Economics, University of Cambridge.
    18. Peter C. B. Phillips & Donggyu Sul, 2009. "Economic transition and growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1153-1185, November.
    19. Guglielmo Caporale & Burcu Erdogan & Vladimir Kuzin, 2015. "Testing stock market convergence: a non-linear factor approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 481-498, August.
    20. Fabio Busetti & Lorenzo Forni & Andrew Harvey & Fabrizio Venditti, 2007. "Inflation Convergence and Divergence within the European Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 3(2), pages 95-121, June.
    21. Castellacci, Fulvio, 2008. "Technology clubs, technology gaps and growth trajectories," Structural Change and Economic Dynamics, Elsevier, vol. 19(4), pages 301-314, December.
    22. K.P. Gluschenko (glu@nsu.ru ), 2010. "Income inequality in Russian regions: comparative analysis," Journal "Region: Economics and Sociology", Institute of Economics and Industrial Engineering of Siberian Branch of RAS, vol. 4.
    23. Lee Kian Lim & Michael McAleer, 2004. "Convergence and catching up in ASEAN: a comparative analysis," Applied Economics, Taylor & Francis Journals, vol. 36(2), pages 137-153.
    24. Marrero, Ángel S. & Marrero, Gustavo A. & González, Rosa Marina & Rodríguez-López, Jesús, 2021. "Convergence in road transport CO2 emissions in Europe," Energy Economics, Elsevier, vol. 99(C).
    25. Michelle Baddeley, 2006. "Convergence or Divergence? The Impacts of Globalisation on Growth and Inequality in Less Developed Countries," International Review of Applied Economics, Taylor & Francis Journals, vol. 20(3), pages 391-410.
    26. Daniel J. Henderson & Christopher F. Parmeter & R. Robert Russell, 2008. "Modes, weighted modes, and calibrated modes: evidence of clustering using modality tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 607-638.
    27. Ulrich Fritsche & Vladimir Kuzin, 2007. "Unit Labor Cost Growth Differentials in the Euro Area, Germany, and the US: Lessons from PANIC and Cluster Analysis," Discussion Papers of DIW Berlin 667, DIW Berlin, German Institute for Economic Research.
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    29. Abbott, Andrew & De Vita, Glauco & Altinay, Levent, 2012. "Revisiting the convergence hypothesis for tourism markets: Evidence from Turkey using the pairwise approach," Tourism Management, Elsevier, vol. 33(3), pages 537-544.
    30. Ulrich Fritsche & Vladimir Kuzin, 2008. "Analysing Convergence in Europe Using a Non-linear Single Factor Model," Macroeconomics and Finance Series 200802, University of Hamburg, Department of Socioeconomics.
    31. Nicholas Apergis & Christina Christou & Stephen Miller, 2012. "Convergence patterns in financial development: evidence from club convergence," Empirical Economics, Springer, vol. 43(3), pages 1011-1040, December.
    32. Alfredo Garcia Hiernaux & David Esteban Guerrero Burbano & Michael McAleer, 2015. "Market Integration Dynamics and Asymptotic Price Convergence in Distribution," Documentos de Trabajo del ICAE 2015-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    33. Mateusz Tomal, 2024. "A review of Phillips‐Sul approach‐based club convergence tests," Journal of Economic Surveys, Wiley Blackwell, vol. 38(3), pages 899-930, July.
    34. Beylunioğlu, Fuat C. & Yazgan, M. Ege & Stengos, Thanasis, 2020. "Detecting Convergence Clubs," Macroeconomic Dynamics, Cambridge University Press, vol. 24(3), pages 629-669, April.
    35. Xu, Ke-Li, 2012. "Robustifying multivariate trend tests to nonstationary volatility," Journal of Econometrics, Elsevier, vol. 169(2), pages 147-154.
    36. Mateusz Tomal, 2022. "Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals," Empirical Economics, Springer, vol. 62(4), pages 2023-2055, April.
    37. Manfred M. Fischer & James P. LeSage, 2015. "A Bayesian space-time approach to identifying and interpreting regional convergence clubs in Europe," Papers in Regional Science, Wiley Blackwell, vol. 94(4), pages 677-702, November.
    38. Claude Diebolt & Tapas Mishra & Bazoumana Ouattara & Mamata Parhi, 2013. "Democracy and Economic Growth in an Interdependent World," Review of International Economics, Wiley Blackwell, vol. 21(4), pages 733-749, September.
    39. German-Soto, Vicente & Gluschenko, Konstantin, 2021. "Long-Run Cross-State Growth Comparison in Mexico," MPRA Paper 109015, University Library of Munich, Germany.
    40. Ozgen Sayginsoy, 2005. "Powerful and Serial Correlation Robust Tests of the Economic Convergence Hypothesis," Econometrics 0503014, University Library of Munich, Germany, revised 11 Mar 2005.
    41. Tirtha Chaterjee & A. Ganesh Kumar, 2014. "Neighborhood and Agricultural Clusters across States of India," Working Papers id:6272, eSocialSciences.
    42. Tommaso Proietti, 2005. "Convergence in Italian regional per-capita GDP," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 497-506.
    43. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergences of prices and rates of inflation," Temi di discussione (Economic working papers) 575, Bank of Italy, Economic Research and International Relations Area.
    44. Castellacci, Fulvio, 2008. "The technology clubs: the distribution of knowledge across nations," MPRA Paper 27597, University Library of Munich, Germany.
    45. Thanasis Stengos & M. Ege Yazgan & Harun Özkan, 2018. "Persistence In Convergence And Club Formation," Bulletin of Economic Research, Wiley Blackwell, vol. 70(2), pages 119-138, April.
    46. Alexandre Almeida & Aurora A.C. Teixeira, 2007. "Does Patenting negatively impact on R&D investment?An international panel data assessment," FEP Working Papers 255, Universidade do Porto, Faculdade de Economia do Porto.
    47. Yilmazkuday, Hakan, 2009. "Inflation Targeting and Inflation Convergence within Turkey," MPRA Paper 16770, University Library of Munich, Germany.
    48. Eberhardt, Markus & Teal, Francis, 2009. "Econometrics for Grumblers: A New Look at the Literature on Cross-Country Growth Empirics," MPRA Paper 15813, University Library of Munich, Germany.
    49. Matsuki, Takashi, 2019. "Per capita output convergence across Asian countries: Evidence from covariate unit root test with an endogenous structural break," Economic Modelling, Elsevier, vol. 82(C), pages 99-118.
    50. Paap, R. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 2003. "Does Africa grow slower than Asia and Latin America?," Econometric Institute Research Papers EI 2003-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    51. Luisa Corrado & Thanasis Stengos & Melvyn Weeks & M. Ege Yazgan, 2019. "Robust Tests for Convergence Clubs," CEIS Research Paper 451, Tor Vergata University, CEIS, revised 14 Feb 2019.
    52. Mariam Camarero & Juana Castillo Giménez & Andrés J. Picazo-Tadeo & Cecilio Tamarit, 2013. "Is the eco-efficiency in greenhouse gas emissions converging among European Union countries?," Working Papers 1309, Department of Applied Economics II, Universidad de Valencia.
    53. Corrado, L. & Martin, R. & Weeks, M., 2004. "Identifying and Interpreting Convergence Clusters Across Europe," Cambridge Working Papers in Economics 0414, Faculty of Economics, University of Cambridge.
    54. Andrea Bonilla, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region's Integration Projects," Working Papers halshs-01069353, HAL.
    55. Paap, Richard & Franses, Philip Hans & van Dijk, Dick, 2005. "Does Africa grow slower than Asia, Latin America and the Middle East? Evidence from a new data-based classification method," Journal of Development Economics, Elsevier, vol. 77(2), pages 553-570, August.
    56. Silva Lopes, Artur, 2016. "A simple proposal to improve the power of income convergence tests," Economics Letters, Elsevier, vol. 138(C), pages 92-95.
    57. Jianning Kong & Peter C.B. Phillips & Donggyu Sul, 2017. "Weak s- Convergence: Theory and Applications," Cowles Foundation Discussion Papers 2072, Cowles Foundation for Research in Economics, Yale University.
    58. Martin Schmidt & David Berri, 2004. "Convergence and clustering in major league baseball: the haves and have nots?," Applied Economics, Taylor & Francis Journals, vol. 36(18), pages 2007-2014.
    59. Westerlund, Joakim & Edgerton, David L. & Opper, Sonja, 2010. "Why is Chinese provincial output diverging?," Journal of Asian Economics, Elsevier, vol. 21(4), pages 333-344, August.
    60. Lin, Zhibin & You, Kefei & Lau, Chi Keung & Demir, Ender, 2019. "Segmenting global tourism markets: A panel club convergence approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 165-185.
    61. Jen-Je Su, 2003. "On the power of the multivariate KPSS test of stationarity against fractionally integrated alternatives," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 637-641.
    62. Fousekis, Panos, 2009. "Are Food Prices in the EU Converging? Empirical Evidence from the Log t Test," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 62(4), pages 407-423.
    63. Esfandiar Maasoumi & Le Wang, 2008. "Economic Reform, Growth and Convergence in China," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 128-154, March.
    64. ArdIc, Oya PInar, 2006. "The gap between the rich and the poor: Patterns of heterogeneity in the cross-country data," Economic Modelling, Elsevier, vol. 23(3), pages 538-555, May.
    65. Massimiliano Affinito, 2011. "Convergence clubs, the euro-area rank and the relationship between banking and real convergence," Temi di discussione (Economic working papers) 809, Bank of Italy, Economic Research and International Relations Area.
    66. Tommaso Proietti & Eric Hillebrand, 2015. "Seasonal Changes in Central England Temperatures," CEIS Research Paper 347, Tor Vergata University, CEIS, revised 15 Jun 2015.
    67. Melanie Krause, 2017. "The Millennium Peak in Club Convergence: A New Look at Distributional Changes in The Wealth of Nations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 621-642, April.
    68. Massimiliano Affinito & Fabio Farabullini, 2006. "An empirical analysis of national differences in the retail bank interest rates of the euro area," Temi di discussione (Economic working papers) 589, Bank of Italy, Economic Research and International Relations Area.
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    70. Nicholas Apergis & Chi Keung Lau, 2022. "Hotel Revenue Convergence: Evidence Across Star Hotels in Chinese Provinces," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 50(1), pages 37-51, June.
    71. Alfredo García-Hiernaux & David E. Guerrero, 2011. "Convergence and Cointegration," Documentos de Trabajo del ICAE 2011-22, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    72. Hobijn, Bart & Franses, Philip Hans, 2001. "Are living standards converging?," Structural Change and Economic Dynamics, Elsevier, vol. 12(2), pages 171-200, July.
    73. Christos Emmanouilides & Panos Fousekis, 2009. "Non-Linear Catching-up and Long-Run Convergence in the Agricultural Productivity of US States," Economics Bulletin, AccessEcon, vol. 29(1), pages 182-189.
    74. Mahamat Hamit-Haggar, 2013. "A note on convergence across Canadian provinces: new insights from the club clustering algorithm," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 591-601, April.
    75. Win Lin Chou & Zijun Wang, 2009. "Regional inequality in China's health care expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 18(S2), pages 137-146, July.
    76. Tsun Se Cheong & Yanrui Wu, 2014. "Convergence and Transitional Dynamics of China's Industrial Output: A County-Level Study Using a New Framework of Distribution Dynamics Analysis," Economics Discussion / Working Papers 14-21, The University of Western Australia, Department of Economics.
    77. Karanasos, M. & Koutroumpis, P. & Karavias, Y. & Kartsaklas, A. & Arakelian, V., 2016. "Inflation convergence in the EMU," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 241-253.
    78. Joseph G. Hirschberg & Esfandiar Maasoumi & Daniel J. Slottje, 2001. "Clusters of attributes and well-being in the USA," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 445-460.
    79. Nalan Baştürk & Richard Paap & Dick van Dijk, 2012. "Structural differences in economic growth: an endogenous clustering approach," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 119-134, January.
    80. Harvey, A. & Vasco Carvalho, 2002. "Models for Converging Economies," Cambridge Working Papers in Economics 0216, Faculty of Economics, University of Cambridge.
    81. Charles Shaaba Saba & Oladipo Olalekan David, 2023. "Identifying Convergence in Telecommunication Infrastructures and the Dynamics of Their Influencing Factors Across Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1413-1466, June.
    82. Up Lim, 2016. "Regional income club convergence in US BEA economic areas: a spatial switching regression approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 273-294, January.
    83. Cheong, Tsun Se & Wu, Yanrui, 2013. "Regional disparity, transitional dynamics and convergence in China," Journal of Asian Economics, Elsevier, vol. 29(C), pages 1-14.
    84. Matsuki, Takashi & Pan, Lei, 2021. "Per capita carbon emissions convergence in developing Asia: A century of evidence from covariate unit root test with endogenous structural breaks," Energy Economics, Elsevier, vol. 99(C).
    85. Fousekis, Panos, 2007. "Convergence of Relative State-level Per Capita Incomes in the United States Revisited," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 37(2), pages 1-10.
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    87. Giles, David E.A. & Feng, Hui, 2005. "Output and well-being in industrialized nations in the second half of the 20th century: testing for convergence using fuzzy clustering analysis," Structural Change and Economic Dynamics, Elsevier, vol. 16(2), pages 285-308, June.
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    89. Francisco Delgado & Maria Jose Presno, 2011. "Convergence of fiscal pressure in the EU: a time series approach," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4257-4267.
    90. Zijun Wang, 2006. "Convergence of productivity: a comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1101-1102, November.
    91. Camarero, Mariam, & Flôres, R. & C. Tamarit, 2002. "Time series evidence of international output convergence in Mercosur," Computing in Economics and Finance 2002 87, Society for Computational Economics.
    92. Andrea Bonilla Bolanos, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region’s Integration Projects," Working Papers 1424, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    93. Zijun Wang, 2009. "The convergence of health care expenditure in the US states," Health Economics, John Wiley & Sons, Ltd., vol. 18(1), pages 55-70, January.
    94. Harry Aginta, 2020. "Does the law of one price hold in 82 Indonesian cities? Evidence from club convergence approach," Economics Bulletin, AccessEcon, vol. 40(4), pages 2844-2858.
    95. Zijun Wang, 2006. "Convergence of productivity: a comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1101-1102.
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    104. Up Lim, 2016. "Regional income club convergence in US BEA economic areas: a spatial switching regression approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 273-294, January.
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  155. Philip Hans Franses & Richard Paap, 2000. "Modelling day-of-the-week seasonality in the S&P 500 index," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 483-488.

    Cited by:

    1. Ahmed Kamaly & Eskandar Tooma, 2009. "Calendar anomolies and stock market volatility in selected Arab stock exchanges," Applied Financial Economics, Taylor & Francis Journals, vol. 19(11), pages 881-892.
    2. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series 015, University of Pavia, Department of Economics and Management.
    3. Saïd Souam & Faycal Hamdi, 2018. "Mixture Periodic GARCH Models: Theory and Applications," Post-Print hal-01589209, HAL.
    4. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    5. Abdelouahab Bibi, 2021. "Asymptotic properties of QMLE for seasonal threshold GARCH model with periodic coefficients," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 477-514, June.
    6. Vicent AragO-Manzana & M Angeles Fernandezizquierdo, 2003. "Monthly seasonality of the returns and volatility of the IBEX-35 index and its futures contract," Applied Economics Letters, Taylor & Francis Journals, vol. 10(3), pages 129-133.
    7. Liu, Tianhao, 2021. "A study on day-of-week effect of submission: Based on the data of JSFST," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    8. Paul Alagidede & Theodore Panagiotidis, 2009. "Calendar Anomalies in the Ghana Stock Exchange," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(1), pages 1-23, April.
    9. M. Berument & Nukhet Dogan, 2012. "Stock market return and volatility: day-of-the-week effect," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(2), pages 282-302, April.
    10. Christian Francq & Roch Roy & Abdessamad Saidi, 2011. "Asymptotic Properties of Weighted Least Squares Estimation in Weak PARMA Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 699-723, November.
    11. Sabina Nowak & Joanna Olbrys, 2015. "Day-of-the-Week Effects in Liquidity on the Warsaw Stock Exchange," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 49-69.
    12. Erik Theissen, 2007. "An analysis of private investors' stock market return forecasts," Applied Financial Economics, Taylor & Francis Journals, vol. 17(1), pages 35-43.
    13. Christos S. Savva & Denise R. Osborn & Len Gill, 2006. "Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US," Centre for Growth and Business Cycle Research Discussion Paper Series 77, Economics, The University of Manchester.
    14. Christian Huurman & Francesco Ravazzolo & Chen Zhou, 2007. "The Power of Weather: Some Empirical Evidence on Predicting Day-ahead Power Prices through Day-ahead Weather Forecasts," Tinbergen Institute Discussion Papers 07-036/4, Tinbergen Institute.
    15. Wessel Marquering & Johan Nisser & Toni Valla, 2006. "Disappearing anomalies: a dynamic analysis of the persistence of anomalies," Applied Financial Economics, Taylor & Francis Journals, vol. 16(4), pages 291-302.
    16. Ausloos, Marcel & Nedic, Olgica & Dekanski, Aleksandar & Mrowinski, Maciej J. & Fronczak, Piotr & Fronczak, Agata, 2017. "Day of the week effect in paper submission/acceptance/rejection to/in/by peer review journals. II. An ARCH econometric-like modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 462-474.
    17. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    18. Stanislav Anatolyev, 2009. "Nonparametric regression (in Russian)," Quantile, Quantile, issue 7, pages 37-52, September.
    19. Bibi, Abdelouahab & Ghezal, Ahmed, 2017. "Asymptotic properties of QMLE for periodic asymmetric strong and semi-strong GARCH models," MPRA Paper 81126, University Library of Munich, Germany.
    20. Am�lie Charles, 2010. "Does the day-of-the-week effect on volatility improve the volatility forecasts?," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 257-262, February.
    21. Roberto Joaquín Santillán Salgado & Alejandro Fonseca Ramírez & Luis Nelson Romero, 2019. "The "day-of-the-week" effects in the exchange rate of Latin American currencies," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(PNEA), pages 485-507, Agosto 20.
    22. Aknouche, Abdelhakim & Bentarzi, Mohamed, 2008. "On the existence of higher-order moments of periodic GARCH models," Statistics & Probability Letters, Elsevier, vol. 78(18), pages 3262-3268, December.
    23. Taylor, James W., 2006. "Density forecasting for the efficient balancing of the generation and consumption of electricity," International Journal of Forecasting, Elsevier, vol. 22(4), pages 707-724.
    24. Ausloos, Marcel & Nedic, Olgica & Dekanski, Aleksandar, 2016. "Day of the week effect in paper submission/acceptance/rejection to/in/by peer review journals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 197-203.

  156. Dijk, Dick van & Franses, Philip Hans, 1999. "Modeling Multiple Regimes in the Business Cycle," Macroeconomic Dynamics, Cambridge University Press, vol. 3(3), pages 311-340, September.
    See citations under working paper version above.
  157. Eisinga, Rob & Franses, Philip Hans & Ooms, Marius, 1999. "Forecasting long memory left-right political orientations," International Journal of Forecasting, Elsevier, vol. 15(2), pages 185-199, April.

    Cited by:

    1. Elliot Tonkes & Dharma Lesmono, 2010. "Consistency in the US Congressional Popular Opinion Polls and Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 4(2), pages 45-64, September.
    2. Pérez, Ana, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Goodell, John W. & McGroarty, Frank & Urquhart, Andrew, 2015. "Political uncertainty and the 2012 US presidential election: A cointegration study of prediction markets, polls and a stand-out expert," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 162-171.
    4. Laura Mayoral & Juan J. Dolado & Jesús Gonzalo, 2003. "Long-range dependence in Spanish political opinion poll series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 137-155.
    5. Lesmono, Dharma & Tonkes, Elliot & Burrage, Kevin, 2009. "Opportunistic timing and manipulation in Australian Federal Elections," European Journal of Operational Research, Elsevier, vol. 192(2), pages 677-691, January.

  158. Richard Paap & Philip Hans Franses, 1999. "On trends and constants in periodic autoregressions," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 271-286.

    Cited by:

    1. del Barrio Castro, Tomás & Osborn, Denise R., 2008. "Cointegration For Periodically Integrated Processes," Econometric Theory, Cambridge University Press, vol. 24(1), pages 109-142, February.
    2. Tomás del Barrio Castro & Gianluca Cubadda & Denise R. Osborn, 2022. "On cointegration for processes integrated at different frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 412-435, May.
    3. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.
    6. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    7. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    8. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    9. del Barrio Castro Tomás & Osborn Denise R, 2011. "Nonparametric Tests for Periodic Integration," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-35, February.
    10. Eugen Ursu & Pierre Duchesne, 2009. "Estimation and model adequacy checking for multivariate seasonal autoregressive time series models with periodically varying parameters," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 183-212, May.

  159. Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, vol. 24(3), pages 427-449.
    See citations under working paper version above.
  160. Franses, Philip Hans & Ghijsels, Hendrik, 1999. "Additive outliers, GARCH and forecasting volatility," International Journal of Forecasting, Elsevier, vol. 15(1), pages 1-9, February.

    Cited by:

    1. Carnero, María Ángeles, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
    3. Patrick F. Patrocinio & Valderio A. Reisen & Pascal Bondon & Edson Z. Monte & Ian M. Danilevicz, 2024. "M-Quantile Estimation for GARCH Models," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2175-2192, June.
    4. Chan, W.S. & Wong, C.S. & Chung, A.H.L., 2009. "Modelling Australian interest rate swap spreads by mixture autoregressive conditional heteroscedastic processes," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2779-2786.
    5. Doornik, Jurgen A. & Ooms, Marius, 2008. "Multimodality in GARCH regression models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 432-448.
    6. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    7. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    8. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    9. Philipp Aschersleben & Winfried J. Steiner, 2022. "A semiparametric approach to estimating reference price effects in sales response models," Journal of Business Economics, Springer, vol. 92(4), pages 591-643, May.
    10. Amélie Charles & Olivier Darné & Laurent Ferrara, 2018. "Does The Great Recession Imply The End Of The Great Moderation? International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 745-760, April.
    11. E. Ruiz & M.A. Carnero & D. Pereira, 2004. "Effects of Level Outliers on the Identification and Estimation of GARCH Models," Econometric Society 2004 Australasian Meetings 21, Econometric Society.
    12. Bali, Rakesh & Guirguis, Hany, 2007. "Extreme observations and non-normality in ARCH and GARCH," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 332-346.
    13. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    14. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    15. Guidi, Francesco, 2010. "Modelling and forecasting volatility of East Asian Newly Industrialized Countries and Japan stock markets with non-linear models," MPRA Paper 19851, University Library of Munich, Germany.
    16. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    17. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
    18. Vadim Azhmyakov & Ilya Shirokov & Luz Adriana Guzman Trujillo, 2024. "Advanced Statistical Analysis of the Predicted Volatility Levels in Crypto Markets," JRFM, MDPI, vol. 17(7), pages 1-15, July.
    19. Fang, WenShwo & Miller, Stephen M., 2009. "Modeling the volatility of real GDP growth: The case of Japan revisited," Japan and the World Economy, Elsevier, vol. 21(3), pages 312-324, August.
    20. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    21. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    22. Giorgio Busetti & Matteo Manera, 2003. "STAR-GARCH Models for Stock Market Interactions in the Pacific Basin Region, Japan and US," Working Papers 2003.43, Fondazione Eni Enrico Mattei.
    23. Jinliang Li & Chihwa Kao & Wei David Zhang, 2010. "Bounded influence estimator for GARCH models: evidence from foreign exchange rates," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1437-1445.
    24. Francq, Christian & Zakoian, Jean-Michel, 2019. "Testing the existence of moments for GARCH processes," MPRA Paper 98892, University Library of Munich, Germany.
    25. Xiaowen Dai & Libin Jin & Anqi Shi & Lei Shi, 2016. "Outlier detection and accommodation in general spatial models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(3), pages 453-475, August.
    26. Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    27. WenShwo Fang & Stephen M. Miller & ChunShen Lee, 2008. "The Great Moderation Flattens Fat Tails: Disappearing Leptokurtosis," Working papers 2008-48, University of Connecticut, Department of Economics.
    28. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    29. Beum-Jo Park, 2009. "Risk-return relationship in equity markets: using a robust GMM estimator for GARCH-M models," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 93-104.
    30. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    31. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    32. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    33. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    34. Mathieu Gatumel & Dominique Guegan, 2008. "Dynamic Analysis of the Insurance Linked Securities Index," Post-Print halshs-00320378, HAL.
    35. Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
    36. Ewa Ratuszny, 2013. "Robust Estimation in VaR Modelling - Univariate Approaches using Bounded Innovation Propagation and Regression Quantiles Methodology," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(1), pages 35-63, March.
    37. Ané, Thierry & Ureche-Rangau, Loredana & Gambet, Jean-Benoît & Bouverot, Julien, 2008. "Robust outlier detection for Asia-Pacific stock index returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 326-343, October.
    38. Nathan Lael Joseph, 2003. "Using monthly returns to model conditional heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 791-801.
    39. Vasiliki Chatzikonstanti & Michail Karoglou, 2022. "Can black swans be tamed with a flexible mean‐variance specification?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3202-3227, July.
    40. PREMINGER, Arie & FRANCK, Raphael, 2007. "Forecasting exchange rates: a robust regression approach," LIDAM Reprints CORE 1917, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    41. Mathieu Gatumel & Dominique Guegan, 2008. "Dynamic Analysis of the Insurance Linked Securities Index," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00320378, HAL.
    42. Veiga, Helena, 2009. "Wavelet-based detection of outliers in volatility models," DES - Working Papers. Statistics and Econometrics. WS ws090403, Universidad Carlos III de Madrid. Departamento de Estadística.
    43. Guermat, Cherif & Harris, Richard D. F., 2002. "Forecasting value at risk allowing for time variation in the variance and kurtosis of portfolio returns," International Journal of Forecasting, Elsevier, vol. 18(3), pages 409-419.
    44. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Post-Print hal-03794543, HAL.
    45. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    46. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.
    47. Wang, Ju-Jie & Wang, Jian-Zhou & Zhang, Zhe-George & Guo, Shu-Po, 2012. "Stock index forecasting based on a hybrid model," Omega, Elsevier, vol. 40(6), pages 758-766.
    48. Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
    49. Lei Shi & Md. Mostafizur Rahman & Wen Gan & Jianhua Zhao, 2015. "Stepwise local influence in generalized autoregressive conditional heteroskedasticity models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 428-444, February.
    50. Watkins, Clinton & McAleer, Michael, 2005. "Related commodity markets and conditional correlations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 567-579.
    51. Guanghui Cai & Zhimin Wu & Lei Peng, 2021. "Forecasting volatility with outliers in Realized GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 667-685, July.
    52. Nagaraj Naik & Biju R. Mohan, 2021. "Stock Price Volatility Estimation Using Regime Switching Technique-Empirical Study on the Indian Stock Market," Mathematics, MDPI, vol. 9(14), pages 1-18, July.
    53. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    54. Grossi Luigi, 2004. "Analyzing Financial Time Series through Robust Estimators," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-15, May.
    55. Dejan Živkov & Jovan Njegić & Mirela Momčilović & Ivan Milenković, 2016. "Exchange Rate Volatility and Uncovered Interest Rate Parity in the European Emerging Economies," Prague Economic Papers, Prague University of Economics and Business, vol. 2016(3), pages 253-270.
    56. Martha Cecilia García & Aura María Jalal & Luis Alfonso Garzón & Jorge Mario López, 2013. "Métodos para predecir índices Bursátiles," Revista Ecos de Economía, Universidad EAFIT, December.
    57. Beine, Michel & Laurent, Sebastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 641-660, December.
    58. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    59. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    60. Thavaneswaran, A. & Appadoo, S.S. & Peiris, S., 2005. "Forecasting volatility," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 1-10, November.
    61. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    62. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    63. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    64. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    65. Mike K. P. So & Wing Ki Liu & Amanda M. Y. Chu, 2018. "Bayesian Shrinkage Estimation Of Time-Varying Covariance Matrices In Financial Time Series," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 369-404, December.
    66. Charles, Amélie & Darné, Olivier, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, Elsevier, vol. 157(C), pages 179-202.
    67. Karakatsani Nektaria V & Bunn Derek W., 2010. "Fundamental and Behavioural Drivers of Electricity Price Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-42, September.
    68. Gilles Daniel & Nathan Joseph & David Bree, 2005. "Stochastic volatility and the goodness-of-fit of the Heston model," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 199-211.
    69. Loredana Ureche-Rangau & Franck Speeg, 2011. "A simple method for variance shift detection at unknown time points," Economics Bulletin, AccessEcon, vol. 31(3), pages 2204-2218.
    70. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    71. Juncal Cunado Eizaguirre & Javier Gomez Biscarri & Fernando Perez de Gracia Hidalgo, 2009. "Financial liberalization, stock market volatility and outliers in emerging economies," Applied Financial Economics, Taylor & Francis Journals, vol. 19(10), pages 809-823.
    72. Chikashi Tsuji, 2016. "Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220711-122, December.
    73. Hotta, Luiz & Trucíos, Carlos, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    74. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    75. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    76. Lavín, Jaime F. & Valle, Mauricio A. & Magner, Nicolás S., 2024. "Stock market pattern recognition using symbol entropy analysis," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    77. Franses, Ph.H.B.F. & van Dijk, D.J.C., 1999. "Outlier detection in the GARCH (1,1) model," Econometric Institute Research Papers EI 9926-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    78. Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    79. Liu, Min & Taylor, James W. & Choo, Wei-Chong, 2020. "Further empirical evidence on the forecasting of volatility with smooth transition exponential smoothing," Economic Modelling, Elsevier, vol. 93(C), pages 651-659.
    80. Yaqoob, Tanzeela & Maqsood, Arfa, 2024. "The potency of time series outliers in volatile models: An empirical analysis of fintech, and mineral resources," Resources Policy, Elsevier, vol. 89(C).
    81. Ercan Balaban & Asli Bayar & Robert Faff, 2006. "Forecasting stock market volatility: Further international evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(2), pages 171-188.
    82. Carnero, María Ángeles, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    83. Jang, Hanwool & Song, Yena & Ahn, Kwangwon, 2020. "Can government stabilize the housing market? The evidence from South Korea," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    84. Xiao-Ming Li, 2014. "Rethinking Long Memory and Structural Breaks in the Forward Premium," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(4), pages 455-485, September.
    85. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.
    86. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    87. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.

  161. Paul De Bruin & Philip Hans Franses, 1999. "Forecasting power-transformed time series data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(7), pages 807-815.

    Cited by:

    1. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    2. Proietti, Tommaso & Lütkepohl, Helmut, 2013. "Does the Box–Cox transformation help in forecasting macroeconomic time series?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 88-99.
    3. Key-Il Shin & Hee-Jeong Kang, 2001. "A study on the effect of power transformation in the ARMA(p,q) model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(8), pages 1019-1028.
    4. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2017. "Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 90-101.
    5. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2010. "To Aggregate or Not to Aggregate: Should decisions and models have the same frequency?," ERIM Report Series Research in Management ERS-2010-046-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  162. Van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(2), pages 217-235, April.
    See citations under working paper version above.
  163. Philip Hans Franses & Robert M. Kunst, 1999. "On the Role of Seasonal Intercepts in Seasonal Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(3), pages 409-433, August.
    See citations under working paper version above.
  164. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.
    See citations under working paper version above.
  165. Philip Franses & Irma Geluk & Paul Van Homelen, 1999. "Modeling Item Nonresponse in Questionnaires," Quality & Quantity: International Journal of Methodology, Springer, vol. 33(2), pages 203-213, May.

    Cited by:

    1. Michele Lalla & Maddalena Cavicchioli, 2020. "Nonresponse and measurement errors in income: matching individual survey data with administrative tax data," Department of Economics 0170, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    2. Jarl Kampen, 2007. "The Impact of Survey Methodology and Context on Central Tendency, Nonresponse and Associations of Subjective Indicators of Government Performance," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(6), pages 793-813, December.

  166. Franses, Philip Hans & Paap, Richard, 1999. "Does Seasonality Influence the Dating of Business Cycle Turning Points?," Journal of Macroeconomics, Elsevier, vol. 21(1), pages 79-92, January.

    Cited by:

    1. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    2. Uctum, Remzi, 2007. "Économétrie des modèles à changement de régimes : un essai de synthèse," L'Actualité Economique, Société Canadienne de Science Economique, vol. 83(4), pages 447-482, décembre.
    3. Matas Mir, Antonio & Osborn, Denise R, 2004. "Seasonal adjustment and the detection of business cycle phases," Working Paper Series 357, European Central Bank.
    4. Yoshihiro Ohtsuka, 2018. "Large Shocks and the Business Cycle: The Effect of Outlier Adjustments," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 143-178, April.
    5. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    6. Franses, Ph.H.B.F. & de Bruin, P., 1999. "Seasonal adjustment and the business cycle in unemployment," Econometric Institute Research Papers EI 9923-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    8. Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
    9. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    10. Dalibor Stevanovic & Stéphane Surprenant & Rachidi Kotchoni, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.
    11. E. Andersson & D. Bock & M. Frisen, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 257-278.

  167. Philip Hans Franses & Bart Hobijn, 1998. "Increasing seasonal variation; unit roots versus shifts in mean and trend," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 14(3), pages 255-261, September.

    Cited by:

    1. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

  168. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.

    Cited by:

    1. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Dekimpe, M.G. & Hanssens, D.M. & Nijs, V.R. & Steenkamp, J-B.E.M., 2003. "Measuring Short- and Long-run Promotional Effectiveness on Scanner Data Using Persistence Modeling," ERIM Report Series Research in Management ERS-2003-087-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Carlomagno, Guillermo, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Janghyeok Yoon & Kwangsoo Kim, 2012. "Detecting signals of new technological opportunities using semantic patent analysis and outlier detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 445-461, February.
    5. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    6. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2006. "Robust Artificial Neural Networks for Pricing of European Options," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 329-351, May.
    7. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. van Heerde, H.J. & Dekimpe, M.G. & Putsis, W.P., 2004. "Marketing Models and the Lucas Critique," ERIM Report Series Research in Management ERS-2004-080-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    9. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    10. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2007. "Consumer confidence in Europe : United in diversity," Other publications TiSEM ea8c3268-2c0b-4fcc-9d4a-6, Tilburg University, School of Economics and Management.
    11. Trost, Robert & Silk, Julian, 2003. "Quantitative Models in Marketing Research,: Philip Hans Franses and Richard Paap (Eds.), Cambridge University Press, Cambridge, UK. (2001), 206 pp. - ISBN 0-521-80166-4, [UK pound]30.00," International Journal of Forecasting, Elsevier, vol. 19(3), pages 535-538.
    12. Dekimpe, M.G. & Hanssens, D.M., 2003. "Persistence Modeling for Assessing Marketing Strategy Performance," ERIM Report Series Research in Management ERS-2003-088-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    13. Harald Van Heerde & Kristiaan Helsen & Marnik G. Dekimpe, 2007. "The Impact of a Product-Harm Crisis on Marketing Effectiveness," Marketing Science, INFORMS, vol. 26(2), pages 230-245, 03-04.
    14. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "The European Consumer: United In Diversity?," ERIM Report Series Research in Management ERS-2005-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  169. Philip Hans Franses & Michael McAleer, 1998. "Testing for Unit Roots and Non‐linear Transformations," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(2), pages 147-164, March.

    Cited by:

    1. Mark J. Holmes, 2005. "New Evidence on Long-Run Output Convergence Among Latin American Countries," Journal of Applied Economics, Taylor & Francis Journals, vol. 8(2), pages 299-319, November.
    2. Franses, Philip Hans & de Bruin, Paul, 2002. "On data transformations and evidence of nonlinearity," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 621-632, September.
    3. Kramer, Walter & Davies, Laurie, 2002. "Testing for unit roots in the context of misspecified logarithmic random walks," Economics Letters, Elsevier, vol. 74(3), pages 313-319, February.
    4. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    5. Madden, Gary G & Savage, Scott J, 1998. "Sources of Australian labour productivity change 1950-1994," MPRA Paper 11452, University Library of Munich, Germany.
    6. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    7. Hector Manuel Zárate Solano & Angélica Rengifo Gómez, 2013. "Forecasting annual inflation with power transformations: the case of inflation targeting countries," Borradores de Economia 756, Banco de la Republica de Colombia.
    8. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    9. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    10. Dilip M. Nachane, 2011. "Selected Problems in the Analysis of Nonstationary & Nonlinear Time Series," Journal of Quantitative Economics, The Indian Econometric Society, vol. 9(1), pages 1-17.
    11. Krämer Walter, 2002. "Statistische Besonderheiten von Finanzzeitreihen / Statistical Properties of Financial Time Series," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(2), pages 210-229, April.
    12. Aparicio, Felipe M., 2003. "On the record properties of integrated time series," DES - Working Papers. Statistics and Econometrics. WS ws036414, Universidad Carlos III de Madrid. Departamento de Estadística.

  170. Philip Hans Franses & Paul van Homelen, 1998. "On forecasting exchange rates using neural networks," Applied Financial Economics, Taylor & Francis Journals, vol. 8(6), pages 589-596.

    Cited by:

    1. Marcos Álvarez-Díaz & Alberto Álvarez, 2002. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0205, Universidade de Vigo, Departamento de Economía Aplicada.
    2. Bou-Hamad, Imad & Jamali, Ibrahim, 2020. "Forecasting financial time-series using data mining models: A simulation study," Research in International Business and Finance, Elsevier, vol. 51(C).
    3. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    4. Adam Fadlalla & Farzaneh Amani, 2014. "Predicting Next Trading Day Closing Price Of Qatar Exchange Index Using Technical Indicators And Artificial Neural Networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 209-223, October.
    5. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    6. Cem Kadilar & Muammer Simsek & Cagdas Hakan Aladag, 2009. "Forecasting The Exchange Rate Series With Ann: The Case Of Turkey," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 9(1), pages 17-29, May.
    7. Rakesh K. Bissoondeeal & Michail Karoglou & Alicia M. Gazely, 2011. "Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(1), pages 127-152, February.
    8. Teresa Aparicio & Dulce Saura, 2013. "Do Exchange Rate Series Present General Dependence? Some Results using Recurrence Quantification Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 5(10), pages 678-686.
    9. Nathan Lael Joseph, 2003. "Using monthly returns to model conditional heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 791-801.
    10. Jiří Trešl, 2011. "Srovnání vybraných metod predikce změn trendu indexu PX [Selected Methods of the Prediction of PX Index Trend Reversal]," Politická ekonomie, Prague University of Economics and Business, vol. 2011(2), pages 184-204.
    11. Malhotra, Rashmi & Malhotra, D. K., 2003. "Evaluating consumer loans using neural networks," Omega, Elsevier, vol. 31(2), pages 83-96, April.
    12. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    13. Marcos Álvarez-Díaz & Shawkat Hammoudeh & Rangan Gupta, 2013. "Detecting Predictable Non-linear Dynamics in Dow Jones Industrial Average and Dow Jones Islamic Market Indices using Nonparametric Regressions," Working Papers 201385, University of Pretoria, Department of Economics.
    14. Michael Dietrich, 2005. "Using simple neural networks to analyse firm activity," Working Papers 2005014, The University of Sheffield, Department of Economics, revised Jul 2005.
    15. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    16. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    17. Ahmad Zubaidi Baharumshah & Liew Khim Sen & Lim Kian Ping, 2003. "Exchange Rates Forecasting Model: An Alternative Estimation Procedure," International Finance 0307005, University Library of Munich, Germany.
    18. Marcos Álvarez-Díaz & Alberto Álvarez, 2003. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0301, Universidade de Vigo, Departamento de Economía Aplicada.

  171. Franses, Philip Hans & Lucas, Andre, 1998. "Outlier Detection in Cointegration Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 459-468, October.

    Cited by:

    1. Borbély, Dóra & Meier, Carsten-Patrick, 2003. "Macroeconomic interval forecasting: the case of assessing the risk of deflation in Germany," Kiel Working Papers 1153, Kiel Institute for the World Economy (IfW Kiel).
    2. Barry Falk & Chun-Hsuan Wang, 2003. "Testing long-run PPP with infinite-variance returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 471-484.
    3. Bosco, Bruno & Parisio, Lucia & Pelagatti, Matteo & Baldi, Fabio, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," International Energy Markets Working Papers 7438, Fondazione Eni Enrico Mattei (FEEM).
    4. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    5. Arranz, Miguel A., 2000. "Outliers robust ECM cointegration test based on the trend components," DES - Working Papers. Statistics and Econometrics. WS 10142, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
    7. Luis A. Rivas & José de Jesús Rojas, 2001. "Precios relativos, inflación subyacente y metas de inflación: un análisis para Nicaragua," Monetaria, CEMLA, vol. 0(3), pages 355-380, julio-sep.
    8. Winkelried, Diego, 2012. "Traspaso del tipo de cambio y metas de inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 23, pages 9-24.
    9. Katarzyna Rosiak-Lada, 2008. "Stylized Facts of Macroeconomics: the Polish Experience," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 20.
    10. Blazsek, Szabolcs & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Hong Li & Yanlin Shi, 2022. "Robust information share measures with an application on the international crude oil markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 555-579, April.
    12. Carlomagno, Guillermo, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Alfred A. Haug, 2002. "Temporal Aggregation and the Power of Cointegration Tests: a Monte Carlo Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 399-412, September.
    14. Georgiev, Iliyan, 2010. "Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables," Journal of Econometrics, Elsevier, vol. 158(1), pages 37-50, September.
    15. Meier, Carsten-Patrick, 2004. "Investigating the impact of an appreciation of the euro in a small macroeconometric model of Germany and the euro area," Kiel Working Papers 1204, Kiel Institute for the World Economy (IfW Kiel).
    16. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    17. Daniel G. Garcés Díaz, 2001. "Determinación del nivel de precios y la dinámica inflacionaria en México," Monetaria, CEMLA, vol. 0(3), pages 241-269, julio-sep.
    18. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    19. Benner Joachim & Meier Carsten-Patrick, 2004. "Prognosegüte alternativer Früh Indikatoren für die Konjunktur in Deutschland / Forecasting Performance of Alternative Indicators for the German Economy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 639-652, December.
    20. Diego Winkelried, 2014. "Exchange rate pass-through and inflation targeting in Peru," Empirical Economics, Springer, vol. 46(4), pages 1181-1196, June.
    21. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    22. Carlos Andrés Perilla Castro, 2001. "Capitales mínimos de los establecimientos de crédito," Monetaria, CEMLA, vol. 0(3), pages 271-353, julio-sep.
    23. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    24. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    25. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    26. Andreas Benedictow & Pål Boug, 2013. "Trade liberalisation and exchange rate pass-through: the case of textiles and wearing apparels," Empirical Economics, Springer, vol. 45(2), pages 757-788, October.
    27. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    28. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    29. Mosab I. Tabash & Mujeeb Saif Mohsen Al-Absy & Azzam Hannoon, 2024. "Modeling the Nexus between European Carbon Emission Trading and Financial Market Returns: Practical Implications for Carbon Risk Reduction and Hedging," JRFM, MDPI, vol. 17(4), pages 1-29, April.
    30. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    31. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.

  172. Breitung, Jörg & Franses, Philip Hans, 1998. "On Phillips–Perron-Type Tests For Seasonal Unit Roots," Econometric Theory, Cambridge University Press, vol. 14(2), pages 200-221, April.
    See citations under working paper version above.
  173. Hans Franses, Philip & Koehler, Anne B., 1998. "A model selection strategy for time series with increasing seasonal variation," International Journal of Forecasting, Elsevier, vol. 14(3), pages 405-414, September.

    Cited by:

    1. Albertson, Kevin & Aylen, Jonathan, 2003. "Forecasting the behaviour of manufacturing inventory," International Journal of Forecasting, Elsevier, vol. 19(2), pages 299-311.
    2. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    3. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    4. John Trevor Coshall, 2005. "A Selection Strategy for Modelling UK Tourism Flows by Air to European Destinations," Tourism Economics, , vol. 11(2), pages 141-158, June.
    5. Martelotte Marcela Cohen & Souza Reinaldo Castro & Silva Eduardo Antônio Barros da, 2017. "Design of Seasonal Adjustment Filter Robust to Variations in the Seasonal Behaviour of Time Series," Journal of Official Statistics, Sciendo, vol. 33(1), pages 155-186, March.

  174. Franses, Philip Hans & Koop, Gary, 1998. "On the sensitivity of unit root inference to nonlinear data transformations," Economics Letters, Elsevier, vol. 59(1), pages 7-15, April.

    Cited by:

    1. Franses, Philip Hans & de Bruin, Paul, 2002. "On data transformations and evidence of nonlinearity," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 621-632, September.
    2. Kramer, Walter & Davies, Laurie, 2002. "Testing for unit roots in the context of misspecified logarithmic random walks," Economics Letters, Elsevier, vol. 74(3), pages 313-319, February.
    3. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    4. Deleersnyder, B. & Geyskens, I. & Gielens, K. & Dekimpe, M.G., 2002. "How Cannibalistic is the Internet Channel?," ERIM Report Series Research in Management ERS-2002-22-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    6. Yang, Zhenlin & Abeysinghe, Tilak, 2002. "An explicit variance formula for the Box-Cox functional form estimator," Economics Letters, Elsevier, vol. 76(2), pages 259-265, July.
    7. Gijsenberg, Maarten J. & Nijs, Vincent R., 2019. "Advertising spending patterns and competitor impact," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 232-250.
    8. Krämer Walter, 2002. "Statistische Besonderheiten von Finanzzeitreihen / Statistical Properties of Financial Time Series," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(2), pages 210-229, April.
    9. Deleersnyder, B. & Geyskens, I. & Gielens, K.J.P. & Dekimpe, M.G., 2002. "How cannibalistic is the internet channel? A study of the newspaper industry in the United Kingdom and the Netherlands," Other publications TiSEM 16dcb25c-7ea9-4c75-bdf6-5, Tilburg University, School of Economics and Management.
    10. Kornelis, Marcel & Dekimpe, Marnik G. & Leeflang, Peter S.H., 2008. "Does competitive entry structurally change key marketing metrics?," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 173-182.
    11. Damen, Sven & Vastmans, Frank & Buyst, Erik, 2016. "The effect of mortgage interest deduction and mortgage characteristics on house prices," Journal of Housing Economics, Elsevier, vol. 34(C), pages 15-29.

  175. Philip Hans Franses & Timothy J. Vogelsang, 1998. "On Seasonal Cycles, Unit Roots, And Mean Shifts," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 231-240, May.

    Cited by:

    1. Broersma, Lourens & Dijk, Jouke van, 2002. "How do Dutch regional labour markets adjust to demand shocks?," Research Report 02D07, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Luis C. Nunes & Paulo M. M. Rodrigues, 2011. "On LM‐type tests for seasonal unit roots in the presence of a break in trend," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(2), pages 108-134, March.
    3. Loh, Chung-Ping A., 2015. "Trends and structural shifts in health tourism: Evidence from seasonal time-series data on health-related travel spending by Canada during 1970–2010," Social Science & Medicine, Elsevier, vol. 132(C), pages 173-180.
    4. da Silva Lopes, Artur C. B., 2001. "The robustness of tests for seasonal differencing to structural breaks," Economics Letters, Elsevier, vol. 71(2), pages 173-179, May.
    5. van Dijk, Dick & Strikholm, Birgit & Teräsvirta, Timo, 2001. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," SSE/EFI Working Paper Series in Economics and Finance 0429, Stockholm School of Economics, revised 01 Jun 2004.
    6. Gustavsson, Patrik & Nordström, Jonas, 1999. "The Impact of Seasonal Unit Roots and Vector ARMA Modeling on Forecasting Monthly Tourism Flows," Working Paper Series 150, Trade Union Institute for Economic Research, revised 01 Jul 2000.
    7. Süleyman Bolat & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2017. "Testing the inflation rates in MENA countries: Evidence from quantile regression approach and seasonal unit root test," Post-Print hal-02000695, HAL.
    8. Bradley Michael D. & Jansen Dennis W., 2000. "Are Business Cycle Dynamics the Same across Countries? Testing Linearity around the Globe," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(2), pages 1-23, July.
    9. Artur C. B. da Silva Lopes & Antonio Montañés, 2004. "The Behavior of HEGY Tests for Quarterly Time Series with Seasonal Mean Shifts," Econometrics 0411010, University Library of Munich, Germany.
    10. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    12. Busetti, Fabio & Taylor, A. M. Robert, 2003. "Testing against stochastic trend and seasonality in the presence of unattended breaks and unit roots," Journal of Econometrics, Elsevier, vol. 117(1), pages 21-53, November.
    13. Sun, Jingwei & Shi, Wendong, 2014. "Aggregation of the generalized fractional processes," Economics Letters, Elsevier, vol. 124(2), pages 258-262.
    14. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    15. Popp, Stephan, 2007. "Modified seasonal unit root test with seasonal level shifts at unknown time," Economics Letters, Elsevier, vol. 97(2), pages 111-117, November.
    16. Niels Haldrup & Antonio Montanés & Andreu Sanso, "undated". "Measurement Errors and Outliers in Seasonal Unit Root Testing," Economics Working Papers 2000-8, Department of Economics and Business Economics, Aarhus University.
    17. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
    18. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    19. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    20. Westerlund, Joakim & Costantini, Mauro & Narayan, Paresh & Popp, Stephan, 2009. "Seasonal Unit Root Tests for Trending and Breaking Series with Application to Industrial Production," Working Papers in Economics 377, University of Gothenburg, Department of Economics.
    21. Hassler, Uwe & Rodrigues, Paulo M. M., 2009. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77565, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    22. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    23. B. da Silva Lopes, Artur C., 2005. "Finite sample effects of pure seasonal mean shifts on Dickey-Fuller tests," MPRA Paper 125, University Library of Munich, Germany, revised May 2006.
    24. Harvey, David I. & Leybourne, Stephen J. & Newbold, Paul, 2002. "Seasonal unit root tests with seasonal mean shifts," Economics Letters, Elsevier, vol. 76(2), pages 295-302, July.
    25. Tomás Barrio & Mariam Camarero & Cecilio Tamarit, 2019. "Testing for Periodic Integration with a Changing Mean," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 45-75, June.
    26. Artur C. B. Da Silva Lopes, 2008. "Finite Sample Effects Of Pure Seasonal Mean Shifts On Dickey–Fuller Tests: A Simulation Study," Manchester School, University of Manchester, vol. 76(5), pages 528-538, September.
    27. Narayan, Paresh Kumar & Popp, Stephan, 2011. "An application of a new seasonal unit root test to inflation," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 707-716, October.
    28. Gallo, Andres & Mason, Paul & Shapiro, Steve & Fabritius, Michael, 2010. "What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price," Energy, Elsevier, vol. 35(10), pages 4126-4141.

  176. Philip Hans Franses & Michael McAleer, 1998. "Cointegration Analysis of Seasonal Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 651-678, December.

    Cited by:

    1. Cubadda, Gianluca & Omtzigt, Pieter, 2003. "Small Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems," Economics & Statistics Discussion Papers esdp03012, University of Molise, Department of Economics.
    2. Younes Ben Zaied & Marie-Estelle Binet, 2015. "Modelling seasonality in residential water demand: the case of Tunisia," Post-Print halshs-01102007, HAL.
    3. Sin, Chor-yiu (CY), 2015. "The economic fundamental and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 298-311.
    4. Saha, Shrabani & Zhang, Zhaoyong, 2013. "Do exchange rates affect consumer prices? A comparative analysis for Australia, China and India," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 128-138.
    5. Diego Winkelried Quezada, 2003. "Indicadores adelantados de la inflación en el Perú," Monetaria, CEMLA, vol. 0(4), pages 345-382, octubre-d.
    6. Héctor A. Valle S., 2003. "Pronósticos de inflación para Guatemala hechos con modelos ARIMA y VAR," Monetaria, CEMLA, vol. 0(4), pages 407-428, octubre-d.
    7. Philip Kostov & John Lingard, 2005. "Seasonally specific model analysis of UK cereals prices," Econometrics 0507014, University Library of Munich, Germany.
    8. Fabio Busetti, 2004. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Econometrics 0411003, University Library of Munich, Germany.
    9. Nikolaos Giannellis & Minoas Koukouritakis, 2009. "Behavioural Equilibrium Exchange Rate and Total Misalignment: Evidence from the Euro Exchange Rate," Working Papers 0901, University of Crete, Department of Economics.
    10. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.
    12. Peter C. B. Phillips & Zhijie Xiao, 1998. "A Primer on Unit Root Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 423-470, December.
    13. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    14. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    15. Olivier Darné, 2003. "Maximum likelihood seasonal cointegration tests for daily data," Economics Bulletin, AccessEcon, vol. 3(18), pages 1-8.
    16. Claudia Arguedas & Jorge Requena, 2003. "La dolarización en Bolivia: una estimación de la elasticidad de sustitución entre monedas," Monetaria, CEMLA, vol. 0(4), pages 383-406, octubre-d.
    17. Jesús R. González García, 2003. "La dinámica del consumo privado en México: un análisis de cointegración con cambios de régimen," Monetaria, CEMLA, vol. 0(4), pages 429-449, octubre-d.

  177. Franses Philip Hans & van Griensven Kasper, 1998. "Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-8, January.

    Cited by:

    1. Marcos Álvarez-Díaz & Alberto Álvarez, 2002. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0205, Universidade de Vigo, Departamento de Economía Aplicada.
    2. Bou-Hamad, Imad & Jamali, Ibrahim, 2020. "Forecasting financial time-series using data mining models: A simulation study," Research in International Business and Finance, Elsevier, vol. 51(C).
    3. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    4. Adam Fadlalla & Farzaneh Amani, 2014. "Predicting Next Trading Day Closing Price Of Qatar Exchange Index Using Technical Indicators And Artificial Neural Networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 209-223, October.
    5. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    6. Rakesh K. Bissoondeeal & Michail Karoglou & Alicia M. Gazely, 2011. "Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(1), pages 127-152, February.
    7. Teresa Aparicio & Dulce Saura, 2013. "Do Exchange Rate Series Present General Dependence? Some Results using Recurrence Quantification Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 5(10), pages 678-686.
    8. Nathan Lael Joseph, 2003. "Using monthly returns to model conditional heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 791-801.
    9. Jiří Trešl, 2011. "Srovnání vybraných metod predikce změn trendu indexu PX [Selected Methods of the Prediction of PX Index Trend Reversal]," Politická ekonomie, Prague University of Economics and Business, vol. 2011(2), pages 184-204.
    10. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    11. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    12. Marcos Álvarez-Díaz & Shawkat Hammoudeh & Rangan Gupta, 2013. "Detecting Predictable Non-linear Dynamics in Dow Jones Industrial Average and Dow Jones Islamic Market Indices using Nonparametric Regressions," Working Papers 201385, University of Pretoria, Department of Economics.
    13. Simonetta Longhi & Peter Nijkamp & Aura Reggianni & Erich Maierhofer, 2005. "Neural Network Modeling as a Tool for Forecasting Regional Employment Patterns," International Regional Science Review, , vol. 28(3), pages 330-346, July.
    14. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    15. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    16. Marcos Álvarez-Díaz & Alberto Álvarez, 2003. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0301, Universidade de Vigo, Departamento de Economía Aplicada.

  178. Veenstra, Albert Willem & Franses, Philip Hans, 1997. "A co-integration approach to forecasting freight rates in the dry bulk shipping sector," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(6), pages 447-458, November.

    Cited by:

    1. Zhi Heng & Tsz Leung Yip, 2018. "Impacts of Kra Canal and its toll structures on tanker traffic," Maritime Policy & Management, Taylor & Francis Journals, vol. 45(1), pages 125-139, January.
    2. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    3. Nikola Kutin & Zakaria Moussa & Thomas Vallée, 2018. "Factors behind the Freight Rates in the Liner Shipping Industry," Working Papers halshs-01828633, HAL.
    4. Michael S. Haigh & Nikos K. Nomikos & David A. Bessler, 2004. "Integration and Causality in International Freight Markets: Modeling with Error Correction and Directed Acyclic Graphs," Southern Economic Journal, John Wiley & Sons, vol. 71(1), pages 145-162, July.
    5. Bai, Xiwen & Lam, Jasmine Siu Lee, 2021. "Freight rate co-movement and risk spillovers in the product tanker shipping market: A copula analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    6. Roar Adland & Pierre Cariou & François-Charles Wolff, 2018. "Comparing transaction-based and expert-generated price indices in the market for offshore support vessels," Working Papers halshs-01843720, HAL.
    7. Prochazka, Vit & Adland, Roar & Wallace, Stein W., 2019. "The value of foresight in the drybulk freight market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 232-245.
    8. Roar Adland & Pierre Cariou & Francois-Charles Wolff, 2017. "What makes a freight market index ?," Post-Print hal-03913228, HAL.
    9. Adland, Roar & Cariou, Pierre & Wolff, Francois-Charles, 2017. "What makes a freight market index? An empirical analysis of vessel fixtures in the offshore market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 150-164.
    10. Zhang, X. & Chen, M.Y. & Wang, M.G. & Ge, Y.E. & Stanley, H.E., 2019. "A novel hybrid approach to Baltic Dry Index forecasting based on a combined dynamic fluctuation network and artificial intelligence method," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 499-516.
    11. Koichiro Hayashi, 2020. "Stationarity of spot freight rates considering supply/demand effect," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-9, December.
    12. Sinem Derindere Koseoglu & Ali Ozgür Karagülle, 2013. "Portfolio Diversification Benefits In Shipping Industry: A Cointegration Approach," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 017-128, December.
    13. Michaelides, Panayotis G. & Konstantakis, Konstantinos N. & Milioti, Christina & Karlaftis, Matthew G., 2015. "Modelling spillover effects of public transportation means: An intra-modal GVAR approach for Athens," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 1-18.
    14. Ionescu Gr. Ion, 2016. "Analysis About The European Shipping And Payment Trends 1975 – 2015," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 8(2), pages 63-67, June.
    15. Yang, Zhongzhen & Jiang, Zhenfeng & Notteboom, Theo & Haralambides, Hercules, 2019. "The impact of ship scrapping subsidies on fleet renewal decisions in dry bulk shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 177-189.
    16. Alizadeh, Amir H. & Talley, Wayne K., 2011. "Vessel and voyage determinants of tanker freight rates and contract times," Transport Policy, Elsevier, vol. 18(5), pages 665-675, September.
    17. Adland, Roar & Benth, Fred Espen & Koekebakker, Steen, 2018. "Multivariate modeling and analysis of regional ocean freight rates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 194-221.
    18. Saeed, Naima & Nguyen, Su & Cullinane, Kevin & Gekara, Victor & Chhetri, Prem, 2023. "Forecasting container freight rates using the Prophet forecasting method," Transport Policy, Elsevier, vol. 133(C), pages 86-107.
    19. Ziaul Haque Munim & Hans-Joachim Schramm, 2021. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 310-327, June.
    20. Kou, Ying & Luo, Meifeng, 2018. "Market driven ship investment decision using the real option approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 714-729.
    21. Roar Adland & David Hansson & Levin von der Wense, 2017. "Valuing cargo flexibility in oil transportation," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(7), pages 803-814, October.
    22. Peng, Zixuan & Shan, Wenxuan & Guan, Feng & Yu, Bin, 2016. "Stable vessel-cargo matching in dry bulk shipping market with price game mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 76-94.
    23. Payman Eslami & Kihyo Jung & Daewon Lee & Amir Tjolleng, 2017. "Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 538-550, August.
    24. Liu, Junlin & Chen, Feier, 2018. "Asymmetric volatility varies in different dry bulk freight rate markets under structure breaks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 316-327.
    25. Javier Población, 2017. "Are recent tanker freight rates stationary?," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 650-666, December.
    26. Su, Miao & Nie, Yufei & Li, Jiankun & Yang, Lin & Kim, Woohyoung, 2024. "Futures markets and the baltic dry index: A prediction study based on deep learning," Research in International Business and Finance, Elsevier, vol. 71(C).
    27. Amir Alizadeh & Wayne Talley, 2011. "Microeconomic determinants of dry bulk shipping freight rates and contract times," Transportation, Springer, vol. 38(3), pages 561-579, May.

  179. Boswijk, H. Peter & Franses, Philip Hans & Haldrup, Niels, 1997. "Multiple unit roots in periodic autoregression," Journal of Econometrics, Elsevier, vol. 80(1), pages 167-193, September.

    Cited by:

    1. Politis, Dimitris, 2016. "HEGY test under seasonal heterogeneity," University of California at San Diego, Economics Working Paper Series qt2q4054kf, Department of Economics, UC San Diego.
    2. Sujata Kar, 2010. "A Periodic Autoregressive Model of Indian WPI Inflation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(3), pages 279-292, August.
    3. Bensalma, Ahmed, 2018. "Two Distinct Seasonally Fractionally Differenced Periodic Processes," MPRA Paper 84969, University Library of Munich, Germany.
    4. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Alexander Vosseler & Enzo Weber, 2017. "Bayesian analysis of periodic unit roots in the presence of a break," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3841-3862, August.
    6. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Philip Hans Franses, 2005. "The Econometric Analysis of Seasonal Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 319-321, March.
    8. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    9. Franses, Ph.H.B.F. & Paap, R., 2005. "Random-Coefficient periodic autoregression," Econometric Institute Research Papers EI 2005-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    11. del Barrio Castro Tomás & Osborn Denise R, 2011. "Nonparametric Tests for Periodic Integration," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-35, February.
    12. Leong, Kenneth & McAleer, Michael, 1999. "Testing the life-cycle permanent income hypothesis using intra-year data for Sweden," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 551-560.
    13. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    14. Haldrup, Niels & Salmon, Mark, 1998. "Representations of I(2) cointegrated systems using the Smith-McMillan form," Journal of Econometrics, Elsevier, vol. 84(2), pages 303-325, June.

  180. Ooms, Marius & Franses, Philip Hans, 1997. "On Periodic Correlations between Estimated Seasonal and Nonseasonal Components in German and U.S. Unemployment," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 470-481, October.

    Cited by:

    1. Marius Ooms & M. Angeles Carnero & Siem Jan Koopman, 2004. "Periodic Heteroskedastic RegARFIMA models for daily electricity spot prices," Econometric Society 2004 Australasian Meetings 158, Econometric Society.
    2. Siem Jan Koopman & Philip Hans Franses, 2002. "Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(5), pages 509-526, December.
    3. Franses, Ph.H.B.F. & de Bruin, P., 1999. "Seasonal adjustment and the business cycle in unemployment," Econometric Institute Research Papers EI 9923-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    5. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2006. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Tinbergen Institute Discussion Papers 06-101/4, Tinbergen Institute.
    6. Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Raymund Abara, 2006. "Estimation and evaluation of asset pricing models with habit formation using Philippine data," Applied Economics Letters, Taylor & Francis Journals, vol. 13(8), pages 493-497.

  181. Franses, Philip Hans & Hoek, Henk & Paap, Richard, 1997. "Bayesian analysis of seasonal unit roots and seasonal mean shifts," Journal of Econometrics, Elsevier, vol. 78(2), pages 359-380, June.
    See citations under working paper version above.
  182. Franses, Philip Hans & Ooms, Marius, 1997. "A periodic long-memory model for quarterly UK inflation," International Journal of Forecasting, Elsevier, vol. 13(1), pages 117-126, March.

    Cited by:

    1. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2010. "Testing Fractional Order of Long Memory Processes: A Monte Carlo Study," Post-Print hal-00486655, HAL.
    2. Marius Ooms & M. Angeles Carnero & Siem Jan Koopman, 2004. "Periodic Heteroskedastic RegARFIMA models for daily electricity spot prices," Econometric Society 2004 Australasian Meetings 158, Econometric Society.
    3. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    4. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    5. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with seasonal-cyclical long memory models," Documents de travail du Centre d'Economie de la Sorbonne b08035, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    6. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    7. Bensalma, Ahmed, 2018. "Two Distinct Seasonally Fractionally Differenced Periodic Processes," MPRA Paper 84969, University Library of Munich, Germany.
    8. Fernando Zarzosa Valdivia, 2020. "Inflation Dynamics in the ABC (Argentina, Brazil and Chile) countries," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 3(2), pages 77-99, Octubre.
    9. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    10. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    11. Christopher F. Baum & John Barkoulas, 2006. "Long-memory forecasting of US monetary indices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 291-302.
    12. Ben Nasr, Adnen & Trabelsi, Abdelwahed, 2005. "Seasonal and Periodic Long Memory Models in the In�ation Rates," MPRA Paper 22690, University Library of Munich, Germany, revised 03 Feb 2006.
    13. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    14. Pérez, Ana, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    16. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    17. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    18. Laura Mayoral, 2015. "The Persistence of Inflation in OECD Countries:a Fractionally Integrated Approach," Working Papers 259, Barcelona School of Economics.
    19. G. K. Randolph TAN, 2004. "Long Memory in Import and Export Price Inflation and Persistence of Shocks to the Terms of Trade," Econometric Society 2004 Far Eastern Meetings 732, Econometric Society.
    20. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    21. Dominique Guegan, 2003. "A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates," Post-Print halshs-00201314, HAL.
    22. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    23. Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    24. Guglielmo Maria Caporale & Marinko Skare, 2014. "Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis," Discussion Papers of DIW Berlin 1395, DIW Berlin, German Institute for Economic Research.
    25. Ye, Xunyu & Gao, Ping & Li, Handong, 2015. "Improving estimation of the fractionally differencing parameter in the SARFIMA model using tapered periodogram," Economic Modelling, Elsevier, vol. 46(C), pages 167-179.
    26. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    27. Luis A. Gil-Alana & Yadollah Dadgar & Rouhollah Nazari, 2019. "Iranian inflation: peristence and structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 398-408, April.

  183. Franses, Philip Hans & Draisma, Gerrit, 1997. "Recognizing changing seasonal patterns using artificial neural networks," Journal of Econometrics, Elsevier, vol. 81(1), pages 273-280, November.

    Cited by:

    1. Zhang, Li & Wang, Lu & Wang, Xunxiao & Zhang, Yaojie & Pan, Zhigang, 2022. "How macro-variables drive crude oil volatility? Perspective from the STL-based iterated combination method," Resources Policy, Elsevier, vol. 77(C).
    2. Tortum, Ahmet & Yayla, Nadir & Çelik, Cafer & Gökdağ, Mahir, 2007. "The investigation of model selection criteria in artificial neural networks by the Taguchi method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 446-468.
    3. Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed & Huang, Xu, 2019. "Forecasting tourism demand with denoised neural networks," Annals of Tourism Research, Elsevier, vol. 74(C), pages 134-154.
    4. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    5. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    6. Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
    7. Moisan, Stella & Herrera, Rodrigo & Clements, Adam, 2018. "A dynamic multiple equation approach for forecasting PM2.5 pollution in Santiago, Chile," International Journal of Forecasting, Elsevier, vol. 34(4), pages 566-581.
    8. Qi, Min & Zhang, Guoqiang Peter, 2001. "An investigation of model selection criteria for neural network time series forecasting," European Journal of Operational Research, Elsevier, vol. 132(3), pages 666-680, August.
    9. Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
    10. Vroomen, Bjorn & Hans Franses, Philip & van Nierop, Erjen, 2004. "Modeling consideration sets and brand choice using artificial neural networks," European Journal of Operational Research, Elsevier, vol. 154(1), pages 206-217, April.
    11. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    12. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
    13. Eisinga, R. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 1997. "Timing of Vote Decision in First and Second Order Dutch Elections 1978-1995: Evidence from Artificial Neural Networks," Econometric Institute Research Papers EI 9733/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  184. De Gooijer, Jan G. & Franses, Philip Hans, 1997. "Forecasting and seasonality," International Journal of Forecasting, Elsevier, vol. 13(3), pages 303-305, September.

    Cited by:

    1. Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
    2. Albertson, Kevin & Aylen, Jonathan, 2003. "Forecasting the behaviour of manufacturing inventory," International Journal of Forecasting, Elsevier, vol. 19(2), pages 299-311.
    3. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.

  185. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.
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  186. Paap, Richard & Franses, Philip Hans & Hoek, Henk, 1997. "Mean shifts, unit roots and forecasting seasonal time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 357-368, September.

    Cited by:

    1. David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
    2. Gustavsson, Patrik & Nordström, Jonas, 1999. "The Impact of Seasonal Unit Roots and Vector ARMA Modeling on Forecasting Monthly Tourism Flows," Working Paper Series 150, Trade Union Institute for Economic Research, revised 01 Jul 2000.
    3. Dillon Alleyne, 2006. "Can Seasonal Unit Root Testing Improve the Forecasting Accuracy of Tourist Arrivals?," Tourism Economics, , vol. 12(1), pages 45-64, March.
    4. Artur C. B. da Silva Lopes & Antonio Montañés, 2004. "The Behavior of HEGY Tests for Quarterly Time Series with Seasonal Mean Shifts," Econometrics 0411010, University Library of Munich, Germany.
    5. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    7. Luetkepohl Helmut & Xu Fang, 2011. "Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-23, February.
    8. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    9. Luciana Crosilla, 2006. "The seasonality of ISAE business and consumer surveys: methodological aspects and empirical evidence," ISAE Working Papers 68, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    10. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    11. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    12. Franses, Ph.H.B.F. & Hoek, H. & Paap, R., 1995. "Bayesian Analysis of Seasonal Unit Roots and Seasonal Mean Shifts," Econometric Institute Research Papers EI 9527-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Harvey, David I. & Leybourne, Stephen J. & Newbold, Paul, 2002. "Seasonal unit root tests with seasonal mean shifts," Economics Letters, Elsevier, vol. 76(2), pages 295-302, July.
    14. Clements, Michael P. & Hendry, David F., 1997. "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, Elsevier, vol. 13(3), pages 341-355, September.
    15. Lorde, Troy & Francis, Brian & Skeete, Stephney, 2008. "Are Shocks to Barbados Long-Stay Visitor Arrivals Permanent or Temporary: A Short Empirical Note," MPRA Paper 95597, University Library of Munich, Germany.

  187. Philip Hans Franses & Bart Hobijn, 1997. "Critical values for unit root tests in seasonal time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(1), pages 25-48.

    Cited by:

    1. Rolando Einar Paz Rodriguez, 2019. "La función de emparejamiento agregada del mercado laboral chileno," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 34(1), pages 85-110, April.
    2. Akdi, Yilmaz & Berument, Hakan & Mümin Cilasun, Seyit, 2006. "The relationship between different price indices: Evidence from Turkey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 483-492.
    3. Domenico Depalo, 2009. "A seasonal unit-root test with Stata," Stata Journal, StataCorp LP, vol. 9(3), pages 422-438, September.
    4. Michael Reutter & Jakob Von Weizsacker & Frank Westermann, 2002. "SeptemBear - A seasonality puzzle in the German stock index DAX," Applied Financial Economics, Taylor & Francis Journals, vol. 12(11), pages 765-769.
    5. Naurin, Abida & Qayyum, Abdul, 2016. "Impact of Oil Price and Its Volatility on Stock Market Index in Pakistan: Bivariate EGARCH Model," MPRA Paper 70636, University Library of Munich, Germany.
    6. Sørensen, Nils Karl, 2002. "Modelling and seasonal forecasting of monthly hotel nights in Denmark," ERSA conference papers ersa02p114, European Regional Science Association.
    7. Diego Vásquez, 2003. "Crecimiento Económico y Concentración Original del Ingreso: Experiencias Internacionales desde 1820," Borradores de Economia 237, Banco de la Republica de Colombia.
    8. Anna Serena Vergori, 2012. "Forecasting Tourism Demand: The Role of Seasonality," Tourism Economics, , vol. 18(5), pages 915-930, October.
    9. Wilmar Alexander Cabrera Rodríguez & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Relación entre el riesgo sistémico del sistema financiero y el sector real: un enfoque FAVAR," Borradores de Economia 810, Banco de la Republica de Colombia.
    10. Harvey, David I. & van Dijk, Dick, 2006. "Sample size, lag order and critical values of seasonal unit root tests," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2734-2751, June.
    11. Tsui, Wai Hong Kan & Ozer Balli, Hatice & Gilbey, Andrew & Gow, Hamish, 2014. "Forecasting of Hong Kong airport's passenger throughput," Tourism Management, Elsevier, vol. 42(C), pages 62-76.
    12. Luis Fernando Melo & Fabio Nieto & Mario Ramos, 2003. "A Leading Index for the Colombian Economic Activity," Borradores de Economia 243, Banco de la Republica de Colombia.
    13. Chia-Lin Chang & Thanchanok Khamkaew & Michael McAleer & Roengchai Tansuchat, 2010. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," KIER Working Papers 719, Kyoto University, Institute of Economic Research.
    14. Olivier Darné & Claude Diebolt, 2002. "A Note on Seasonal Unit Root Tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(3), pages 305-310, August.
    15. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu & Kyophilavong, Phouphet, 2015. "Frequency domain causality analysis of stock market and economic activity in India," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 224-238.
    16. Hamori, Shigeyuki, 2001. "Seasonality and stock returns: some evidence from Japan," Japan and the World Economy, Elsevier, vol. 13(4), pages 463-481, December.
    17. Juncal Cuñado & Luis A. Gil-Alaña, 2007. "Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models," Faculty Working Papers 02/07, School of Economics and Business Administration, University of Navarra.
    18. Chang, C-L. & Khamkaew, T. & McAleer, M.J., 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," Econometric Institute Research Papers EI 2010-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Maurice J. Roche & Kieran McQuinn, 2003. "Grain price volatility in a small open economy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 30(1), pages 77-98, March.
    20. Möbert, Jochen, 2007. "Crude Oil Price Determinants," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 35713, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Kavussanos, Manolis G. & Alizadeh-M, Amir H., 2002. "Seasonality patterns in tanker spot freight rate markets," Economic Modelling, Elsevier, vol. 19(5), pages 747-782, November.
    22. Jesus Otero & Manuel Ramirez, 2002. "On the determinants of the inflation rate in Colombia: a disequilibrium market approach," Borradores de Investigación 3296, Universidad del Rosario.
    23. Nitin, Arora & Asghar, OsatiEraghi, 2016. "Does India have a stable demand for money function after reforms? A macroeconometric analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 44, pages 25-37.
    24. Walker, Douglas M. & Jackson, John D., 1998. "New Goods and Economic Growth: Evidence from Legalized Gambling," The Review of Regional Studies, Southern Regional Science Association, vol. 28(2), pages 47-70, Fall.
    25. Marc Lavoie & Gabriel Rodríguez, 2005. "The Economic Impact of Professional Teams on Monthly Hotel Occupancy Rates of Canadian Cities," Journal of Sports Economics, , vol. 6(3), pages 314-324, August.
    26. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    27. Nga, Nguyen Thi Duong & Lantican, Flordeliza A., 2009. "Spatial Integration of Rice Markets in Vietnam," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 6(01), pages 1-16, June.
    28. Aviral Kumar Tiwari & Subhendu Dutta & Aruna Kumar Dash, 2017. "Testing of the Seasonal Unit Root Hypothesis in the Price Indices of Agricultural Commodities in India," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 14(2), pages 63-81, December.
    29. Wai Hong Kan Tsui & Faruk Balli, 2017. "International arrivals forecasting for Australian airports and the impact of tourism marketing expenditure," Tourism Economics, , vol. 23(2), pages 403-428, March.
    30. T Lorde & B Francis & A Greene, 2009. "Testing for Long-Run Comovement, Common Features and Efficiency in Emerging Stock Markets: Evidence from the Caribbean," Economic Issues Journal Articles, Economic Issues, vol. 14(2), pages 55-80, September.
    31. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    32. Tomás del Barrio Castro & Andrii Bodnar & Andreu Sansó Rosselló, 2015. "Numerical Distribution Functions for Seasonal Unit Root Tests with OLS and GLS Detrending," DEA Working Papers 73, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    33. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    34. Josef Arlt, 2023. "The problem of annual inflation rate indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2772-2788, July.
    35. Johann Burgstaller, 2003. "Interest Rate Transmission to Commercial Credit Rates in Austria," Economics working papers 2003-06, Department of Economics, Johannes Kepler University Linz, Austria.
    36. Pedro M. G. Martins, 2010. "Do Capital Inflows Hinder Competitiveness? The Real Exchange Rate in Ethiopia," Working Paper Series 1110, Department of Economics, University of Sussex Business School.
    37. Michael Browne, 2016. "Liquidity effects on consumers’ imports in Trinidad and Tobago," Working Papers 2016-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    38. Anna Serena Vergori, 2017. "Patterns of seasonality and tourism demand forecasting," Tourism Economics, , vol. 23(5), pages 1011-1027, August.
    39. Niels Haldrup & Antonio Montanés & Andreu Sanso, "undated". "Measurement Errors and Outliers in Seasonal Unit Root Testing," Economics Working Papers 2000-8, Department of Economics and Business Economics, Aarhus University.
    40. Jason B. Jorgensen & Fred Joutz, 2012. "Modelling and Forecasting Residential Electricity Consumption in the U.S. Mountain Region," Working Papers 2012-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    41. Otero, Jesús & Smith, Jeremy & Giulietti, Monica, 2008. "Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence," The Warwick Economics Research Paper Series (TWERPS) 865, University of Warwick, Department of Economics.
    42. Pedro M G Martins, 2010. "Fiscal Dynamics in Ethiopia: A Cointegrated VAR Model with Quarterly Data," Discussion Papers 10/05, University of Nottingham, CREDIT.
    43. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    44. Akarapong Untong & Vicente Ramos & Mingsarn Kaosa-Ard & Javier Rey-Maquieira, 2014. "Thailand's Long-Run Tourism Demand Elasticities," Tourism Economics, , vol. 20(3), pages 595-610, June.
    45. Shin, Dong Wan & So, Beong Soo, 2000. "Gaussian tests for seasonal unit roots based on Cauchy estimation and recursive mean adjustments," Journal of Econometrics, Elsevier, vol. 99(1), pages 107-137, November.
    46. Sergey Drobyshevsky & G.Kuzmicheva & Elena Sinelnikova & Pavel Trunin, 2010. "Modeling monetary demand in the Russian economy over 1999–2008," Research Paper Series, Gaidar Institute for Economic Policy, issue 136P.
    47. Sandra G. Feltham & David E.A. Giles, 1999. "Testing for Unit Roots in Semi-Annual Data," Econometrics Working Papers 9912, Department of Economics, University of Victoria.
    48. Tiwari, Aviral, 2010. "Is trade deficit sustainable in India? An inquiry," MPRA Paper 24451, University Library of Munich, Germany.
    49. Pedro Martins, 2011. "Do large capital inflows hinder competitiveness? The Dutch disease in Ethiopia," Post-Print hal-00748067, HAL.
    50. Rotger, Gabriel Pons, "undated". "Testing for Seasonal Unit Roots with Temporally Aggregated Time Series," Economics Working Papers 2003-16, Department of Economics and Business Economics, Aarhus University.
    51. Pedro M G Martins, 2010. "Capital Inflows Hinder Competitiveness? The Real Exchange Rate in Ethiopia," Discussion Papers 10/07, University of Nottingham, CREDIT.
    52. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    53. Hassler, Uwe & Rodrigues, Paulo M. M., 2009. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77565, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    54. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    55. Shigeyuki Hamori & Akira Tokihisa, 2002. "Some International Evidence on the Seasonality of Stock Prices," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(1), pages 79-86, April.
    56. Möbert, Jochen, 2007. "Crude oil price determinants," Darmstadt Discussion Papers in Economics 186, Darmstadt University of Technology, Department of Law and Economics.
    57. Naurin, Abida & Qayyum, Abdul, 2016. "Impact of Oil Price and Its Volatility on CPI of Pakistan: Bivariate EGARCH Model," MPRA Paper 69774, University Library of Munich, Germany.
    58. Ahmed, Syed Shujaat, 2019. "Oil Prices and Exchange Rate with Impact of Pre-Dollar and Post-Dollar Regime Dummies," MPRA Paper 92313, University Library of Munich, Germany.
    59. Denise Osborn & Paulo Rodrigues, 2002. "Asymptotic Distributions Of Seasonal Unit Root Tests: A Unifying Approach," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 221-241.
    60. Maria Blangiewicz & Krystyna Strzala, 2008. "Notes on a Forecasting Procedure," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 8, pages 75-84.
    61. Pedro M. G. Martins, 2010. "Fiscal Dynamics in Ethiopia: The Cointegrated VAR Model with Quarterly Data," Working Paper Series 0910, Department of Economics, University of Sussex Business School.

  188. Philip Hans Franses & Reinoud leperen & Paul Kofman & Martin Martens & Bert Menkveld, 1997. "Volatility Transmission And Patterns In Bund Futures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 20(4), pages 459-482, December.

    Cited by:

    1. Aboura, Sofiane & Chevallier, Julien, 2014. "Cross-market spillovers with ‘volatility surprise’," Review of Financial Economics, Elsevier, vol. 23(4), pages 194-207.
    2. Deqing Diane Li & YingChou Lin & John Jin, 2012. "International Volatility Transmission Of Reit Returns," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 6(3), pages 41-51.
    3. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," Working Papers hal-04141310, HAL.
    4. Helena Chuliá & Hipòlit Torró, 2008. "The economic value of volatility transmission between the stock and bond markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(11), pages 1066-1094, November.
    5. Stevenson, Alan & Boyd, Milton S., 2001. "Lead Lag Relationships Between Resource Prices and Corresponding Resource Company Share Prices," 2001 Conference (45th), January 23-25, 2001, Adelaide, Australia 125959, Australian Agricultural and Resource Economics Society.
    6. Yang, Joey Wenling, 2011. "Transaction duration and asymmetric price impact of trades--Evidence from Australia," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 91-102, January.
    7. Christopher L. Gilbert & Herbert A. Rijken, 2006. "How is Futures Trading Affected by the Move to a Computerized Trading System? Lessons from the LIFFE FTSE 100 Contract," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(7‐8), pages 1267-1297, September.

  189. Franses, Philip Hans & Kleibergen, Frank, 1996. "Unit roots in the Nelson-Plosser data: Do they matter for forecasting?," International Journal of Forecasting, Elsevier, vol. 12(2), pages 283-288, June.

    Cited by:

    1. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    2. Mohitosh Kejriwal & Xuewen Yu, 2019. "Generalized Forecasr Averaging in Autoregressions with a Near Unit Root," Purdue University Economics Working Papers 1318, Purdue University, Department of Economics.
    3. Diebold, Francis X & Kilian, Lutz, 2000. "Unit-Root Tests Are Useful for Selecting Forecasting Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 265-273, July.
    4. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
    5. Franco Bevilacqua & Adriaan van Zon, 2002. "Random Walks and Non-Linear Paths in Macroeconomic Time Series: Some Evidence and Implications," Working Papers geewp22, Vienna University of Economics and Business Research Group: Growth and Employment in Europe: Sustainability and Competitiveness.
    6. Kornelis, Marcel & Dekimpe, Marnik G. & Leeflang, Peter S.H., 2008. "Does competitive entry structurally change key marketing metrics?," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 173-182.
    7. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia.
    8. Min, Chung-ki, 1998. "A Gibbs sampling approach to estimation and prediction of time-varying-parameter models," Computational Statistics & Data Analysis, Elsevier, vol. 27(2), pages 171-194, April.

  190. Rob Eisinga & Philip Franses, 1996. "Testing for convergence in left-right ideological positions," Quality & Quantity: International Journal of Methodology, Springer, vol. 30(4), pages 345-359, November.

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    1. André Krouwel & Annemarie Elfrinkhof, 2014. "Combining strengths of methods of party positioning to counter their weaknesses: the development of a new methodology to calibrate parties on issues and ideological dimensions," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1455-1472, May.

  191. H. Peter Boswijk & Philip Hans Franses, 1996. "Unit Roots In Periodic Autoregressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(3), pages 221-245, May.

    Cited by:

    1. del Barrio Castro, Tomas, 2006. "On the performance of the DHF tests against nonstationary alternatives," Statistics & Probability Letters, Elsevier, vol. 76(3), pages 291-297, February.
    2. del Barrio Castro, Tomás & Osborn, Denise R., 2008. "Cointegration For Periodically Integrated Processes," Econometric Theory, Cambridge University Press, vol. 24(1), pages 109-142, February.
    3. Marius Ooms & M. Angeles Carnero & Siem Jan Koopman, 2004. "Periodic Heteroskedastic RegARFIMA models for daily electricity spot prices," Econometric Society 2004 Australasian Meetings 158, Econometric Society.
    4. Novales, Alfonso & de Fruto, Rafael Flores, 1997. "Forecasting with periodic models A comparison with time invariant coefficient models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 393-405, September.
    5. Antoine Martin & Cyril Monnet, 2008. "Marcos de implementación de la política monetaria: un análisis comparativo," Monetaria, CEMLA, vol. 0(2), pages 221-262, julio-sep.
    6. Richard J. Smith & A. M. Robert Taylor & Tomas del Barrio Castro, 2007. "Regression-based seasonal unit root tests," Discussion Papers 07/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    7. Del Barrio Castro, T & Rodrigues, PMM & Taylor, AMR, 2015. "Semi-Parametric Seasonal Unit Root Tests," Essex Finance Centre Working Papers 16807, University of Essex, Essex Business School.
    8. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    9. Tomas Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2015. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Empirical Economics, Springer, vol. 49(2), pages 389-402, September.
    10. Castro, Tomás del Barrio & Osborn, Denise R. & Taylor, A.M. Robert, 2012. "On Augmented Hegy Tests For Seasonal Unit Roots," Econometric Theory, Cambridge University Press, vol. 28(5), pages 1121-1143, October.
    11. Fernando N. de Oliveira, 2008. "Canal de crédito bancario en Brasil: evidencia de la oferta de crédito bancario y de la composición del financiamiento externo de las empresas," Monetaria, CEMLA, vol. 0(2), pages 175-220, julio-sep.
    12. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Papers 9510, Tilburg - Center for Economic Research.
    13. Shin, Dong Wan & Lee, Oesook, 2007. "Asymmetry and nonstationarity for a seasonal time series model," Journal of Econometrics, Elsevier, vol. 136(1), pages 89-114, January.
    14. Tomás del Barrio Castro & Gianluca Cubadda & Denise R. Osborn, 2022. "On cointegration for processes integrated at different frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 412-435, May.
    15. Clements, Michael & Smith, Jeremy, 1997. "Forecasting Seasonal UK Consumption Components," The Warwick Economics Research Paper Series (TWERPS) 479, University of Warwick, Department of Economics.
    16. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "The trade balance in euro countries: a natural case study of periodic integration with a changing mean," Working Papers 1321, Department of Applied Economics II, Universidad de Valencia.
    18. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    19. Alexander Vosseler & Enzo Weber, 2018. "Forecasting seasonal time series data: a Bayesian model averaging approach," Computational Statistics, Springer, vol. 33(4), pages 1733-1765, December.
    20. A.S.M. Arroyo & A. de Juan Fern¨¢ndez, 2014. "Split-then-Combine Method for out-of-sample Combinations of Forecasts," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 3(1), pages 19-37, April.
    21. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.
    22. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
    23. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.
    24. Luis Fernando Melo Velandia & Óscar Reinaldo Becerra Camargo, 2008. "Una descripción de la dinámica de las tasas de interés de corto plazo en Colombia," Monetaria, CEMLA, vol. 0(2), pages 145-173, julio-sep.
    25. Tomas del Barrio Castro, 2007. "Using the HEGY Procedure When Not All Roots Are Present," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(6), pages 910-922, November.
    26. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    27. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    28. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    29. Elizabeth Bucacos, 2008. "Real (effective) exchange rate in Uruguay: a periodic cointegration approach," Monetaria, CEMLA, vol. 0(2), pages 265-289, julio-sep.
    30. Koopman, Siem Jan & Ooms, Marius & Carnero, M. Angeles, 2007. "Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 16-27, March.
    31. Fantazziini, Dean, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data," MPRA Paper 59696, University Library of Munich, Germany.
    32. Shin, Dong Wan & So, Beong Soo, 2000. "Gaussian tests for seasonal unit roots based on Cauchy estimation and recursive mean adjustments," Journal of Econometrics, Elsevier, vol. 99(1), pages 107-137, November.
    33. Evans, Mark, 2006. "A study of the relationship between regional ferrous scrap prices in the USA, 1958-2004," Resources Policy, Elsevier, vol. 31(2), pages 65-77, June.
    34. Herwartz, Helmut, 1997. "Performance of periodic error correction models in forecasting consumption data," International Journal of Forecasting, Elsevier, vol. 13(3), pages 421-431, September.
    35. del Barrio Castro Tomás & Osborn Denise R, 2011. "Nonparametric Tests for Periodic Integration," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-35, February.
    36. Eugen Ursu & Pierre Duchesne, 2009. "Estimation and model adequacy checking for multivariate seasonal autoregressive time series models with periodically varying parameters," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 183-212, May.
    37. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    38. Abdelhakim Aknouche & Bader Almohaimeed & Stefanos Dimitrakopoulos, 2022. "Periodic autoregressive conditional duration," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 5-29, January.
    39. Burridge, Peter & Taylor, A. M. Robert, 2001. "On regression-based tests for seasonal unit roots in the presence of periodic heteroscedasticity," Journal of Econometrics, Elsevier, vol. 104(1), pages 91-117, August.
    40. Tomás Barrio & Mariam Camarero & Cecilio Tamarit, 2019. "Testing for Periodic Integration with a Changing Mean," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 45-75, June.
    41. Maekawa, Koichi, 1997. "Periodically integrated autoregression with a structural break," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 467-473.
    42. Denise Osborn & Paulo Rodrigues, 2002. "Asymptotic Distributions Of Seasonal Unit Root Tests: A Unifying Approach," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 221-241.
    43. Boswijk, H. Peter & Franses, Philip Hans & Haldrup, Niels, 1997. "Multiple unit roots in periodic autoregression," Journal of Econometrics, Elsevier, vol. 80(1), pages 167-193, September.
    44. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    45. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.

  192. Franses, Philip Hans & Boswijk, H. Peter, 1996. "Temporal aggregation in a periodically integrated autoregressive process," Statistics & Probability Letters, Elsevier, vol. 30(3), pages 235-240, October.
    See citations under working paper version above.
  193. Franses, Philip Hans, 1996. "Recent Advances in Modelling Seasonality," Journal of Economic Surveys, Wiley Blackwell, vol. 10(3), pages 299-345, September.

    Cited by:

    1. Seungmoon Choi, 2011. "Closed-Form Likelihood Expansions for Multivariate Time-Inhomogeneous Diffusions," School of Economics and Public Policy Working Papers 2011-26, University of Adelaide, School of Economics and Public Policy.
    2. Linsenmeier, Manuel, 2024. "Seasonal temperature variability and economic cycles," Journal of Macroeconomics, Elsevier, vol. 79(C).
    3. Philip Hans Franses & Yoshinori Kawasaki, 2004. "Do seasonal unit roots matter for forecasting monthly industrial production?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 77-88.
    4. Linsenmeier, Manuel, 2021. "Seasonal temperature variability and economic cycles," LSE Research Online Documents on Economics 115530, London School of Economics and Political Science, LSE Library.
    5. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    6. De Gooijer, Jan G. & Franses, Philip Hans, 1997. "Forecasting and seasonality," International Journal of Forecasting, Elsevier, vol. 13(3), pages 303-305, September.
    7. Hecq, Alain, 1998. "Does seasonal adjustment induce common cycles?," Economics Letters, Elsevier, vol. 59(3), pages 289-297, June.
    8. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    9. Rodrigues, P.M.M. & Franses, Ph.H.B.F., 2003. "A sequential approach to testing seasonal unit roots in high frequency data," Econometric Institute Research Papers EI 2003-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Bohl, Martin T., 2000. "Nonstationary stochastic seasonality and the German M2 money demand function," European Economic Review, Elsevier, vol. 44(1), pages 61-70, January.
    11. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
    12. Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
    13. Elena Barton & Basad Al-Sarray & Stéphane Chrétien & Kavya Jagan, 2018. "Decomposition of Dynamical Signals into Jumps, Oscillatory Patterns, and Possible Outliers," Mathematics, MDPI, vol. 6(7), pages 1-13, July.
    14. Gianluca Cubadda, 1999. "Common cycles in seasonal non‐stationary time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 273-291, May.
    15. Lalouette, Laure & Zamora-Pérez, Alejandro & Rusu, Codruta & Bartzsch, Nikolaus & Politronacci, Emmanuelle & Delmas, Martial & Rua, António & Brandi, Marco & Naksi, Martti, 2021. "Foreign demand for euro banknotes," Occasional Paper Series 253, European Central Bank.
    16. H. M. Ertugrul & S. Yildirim & F. Ayhan, 2017. "An Investigation of Stationarity Properties of the Turkish Tourism Income Variable," International Econometric Review (IER), Econometric Research Association, vol. 9(2), pages 37-49, September.
    17. Evans, Mark, 2006. "A study of the relationship between regional ferrous scrap prices in the USA, 1958-2004," Resources Policy, Elsevier, vol. 31(2), pages 65-77, June.
    18. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    19. Yoshinori Kawasaki, 1996. "A Model Selection Approach to detect Seasonal Unit Roots," Tinbergen Institute Discussion Papers 96-180/7, Tinbergen Institute.
    20. Emanuela Marrocu, 2006. "An Investigation of the Effects of Data Transformation on Nonlinearity," Empirical Economics, Springer, vol. 31(4), pages 801-820, November.
    21. Jorge Ridderstaat & Peter Nijkamp, 2013. "Measuring Pattern, Amplitude and Timing Differences between Monetary and Non-Monetary Seasonal Factors of Tourism - the Case of Aruba," Tinbergen Institute Discussion Papers 13-116/VIII, Tinbergen Institute, revised 05 Sep 2013.
    22. Tucker McElroy & Anindya Roy, 2022. "A Review of Seasonal Adjustment Diagnostics," International Statistical Review, International Statistical Institute, vol. 90(2), pages 259-284, August.
    23. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    24. Marta Skrzypczyńska, 2014. "Cyclical Processes in the Polish Economy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(3), pages 153-192, September.
    25. Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    27. Clements, Michael P. & Hendry, David F., 1997. "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, Elsevier, vol. 13(3), pages 341-355, September.
    28. Linsenmeier, Manuel, 2024. "Seasonal temperature variability and economic cycles," LSE Research Online Documents on Economics 120640, London School of Economics and Political Science, LSE Library.
    29. Benoit Faye & Éric Le Fur, 2010. "L'étude du lien entre cycle et saisonnalité sur un marché immobilier résidentiel. Le cas de l'habitat ancien à Bordeaux," Revue d'économie régionale et urbaine, Armand Colin, vol. 0(5), pages 937-965.
    30. Yoshinori Kawasaki & Philip Hans Franses, 2003. "Detecting seasonal unit roots in a structural time series model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(4), pages 373-387.

  194. Franses, Philip Hans & Paap, Richard, 1995. "Seasonality and Stochastic Trends in German Consumption and Income, 1960.1-1987.4," Empirical Economics, Springer, vol. 20(1), pages 109-132.

    Cited by:

    1. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Hansen, Hermann-Josef, 1996. "Der Einfluß der Zinsen auf den privaten Verbrauch in Deutschland," Discussion Paper Series 1: Economic Studies 1996,03, Deutsche Bundesbank.
    3. Hassler Uwe, 2001. "Wealth and Consumption. A Multicointegrated Model for the Unified Germany / Vermögen und Konsum. Ein multikointegriertes Modell für das vereinigte Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 221(1), pages 32-44, February.

  195. Franses, Philip Hans & Hylleberg, Svend & Lee, Hahn S., 1995. "Spurious deterministic seasonality," Economics Letters, Elsevier, vol. 48(3-4), pages 249-256, June.

    Cited by:

    1. Robin L. Lumsdaine & Mr. Eswar S Prasad, 1999. "Identifying the Common Component in International Economic Fluctuations: A New Approach," IMF Working Papers 1999/154, International Monetary Fund.
    2. da Silva Lopes, Artur C. B., 2001. "The robustness of tests for seasonal differencing to structural breaks," Economics Letters, Elsevier, vol. 71(2), pages 173-179, May.
    3. Rodrigues, Paulo M. M. & Taylor, A. M. Robert, 2004. "Alternative estimators and unit root tests for seasonal autoregressive processes," Journal of Econometrics, Elsevier, vol. 120(1), pages 35-73, May.
    4. Considine, Timothy J., 2000. "The impacts of weather variations on energy demand and carbon emissions," Resource and Energy Economics, Elsevier, vol. 22(4), pages 295-314, October.
    5. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    6. Franses, Philip Hans & Kunst, Robert M., 2007. "Analyzing a panel of seasonal time series: Does seasonality in industrial production converge across Europe?," Economic Modelling, Elsevier, vol. 24(6), pages 954-968, November.
    7. Lee, H.S. & Siklos, P.L., 1997. "The Role of Seasonality in Economic Time Series: Reinterpretating Money-Output Causality in U.S. Data," Working Papers 97-1, Wilfrid Laurier University, Department of Economics.
    8. Artur C. B. da Silva Lopes, 2004. "Deterministic Seasonality in Dickey-Fuller Tests: Should We Care?," Econometrics 0402007, University Library of Munich, Germany, revised 18 Mar 2004.
    9. Bradley Michael D. & Jansen Dennis W., 2000. "Are Business Cycle Dynamics the Same across Countries? Testing Linearity around the Globe," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(2), pages 1-23, July.
    10. Lee G. Cooper & Penny Baron & Wayne Levy & Michael Swisher & Paris Gogos, 1999. "PromoCast™: A New Forecasting Method for Promotion Planning," Marketing Science, INFORMS, vol. 18(3), pages 301-316.
    11. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    12. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    13. Osborn, Denise R. & Heravi, Saeed & Birchenhall, C. R., 1999. "Seasonal unit roots and forecasts of two-digit European industrial production," International Journal of Forecasting, Elsevier, vol. 15(1), pages 27-47, February.
    14. Ghassen El Montasser & Talel Boufateh & Fakhri Issaoui, 2013. "The Seasonal KPSS Test When Neglecting Seasonal Dummies: A Monte Carlo analysis," EERI Research Paper Series EERI RP 2013/07, Economics and Econometrics Research Institute (EERI), Brussels.
    15. Syed Kalim Hyder Bukhari & Abdul Jalil & Nasir Hamid Rao, 2011. "Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited," SBP Working Paper Series 39, State Bank of Pakistan, Research Department.
    16. Anna Serena Vergori, 2017. "Patterns of seasonality and tourism demand forecasting," Tourism Economics, , vol. 23(5), pages 1011-1027, August.
    17. Adusei Jumah & Robert M. Kunst, 2008. "Seasonal prediction of European cereal prices: good forecasts using bad models?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 391-406.
    18. Leschinski, Christian & Sibbertsen, Philipp, 2019. "Model order selection in periodic long memory models," Econometrics and Statistics, Elsevier, vol. 9(C), pages 78-94.
    19. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    20. Voges, Michelle & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks," Hannover Economic Papers (HEP) dp-599, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    21. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    22. Robin L. Lumsdaine & Eswar S. Prasad, 1997. "Identifying the Common Component in International Economic Fluctuations," NBER Working Papers 5984, National Bureau of Economic Research, Inc.
    23. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  196. Franses, Philip Hans, 1995. "Quarterly US Unemployment: Cycles, Seasons and Asymmetries," Empirical Economics, Springer, vol. 20(4), pages 717-725.

    Cited by:

    1. Siem Jan Koopman & Philip Hans Franses, 2002. "Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(5), pages 509-526, December.
    2. Siem Jan Koopman & Kai Ming Lee, 0000. "Seasonality with Trend and Cycle Interactions in Unobserved Components Models," Tinbergen Institute Discussion Papers 08-028/4, Tinbergen Institute.
    3. Alexander Vosseler & Enzo Weber, 2017. "Bayesian analysis of periodic unit roots in the presence of a break," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3841-3862, August.
    4. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    5. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    6. Stevens, Philip Andrew, 2007. "Skill shortages and firms' employment behaviour," Labour Economics, Elsevier, vol. 14(2), pages 231-249, April.

  197. Franses, Philip Hans & Paap, Richard, 1995. "Moving average filters and periodic integration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 245-249.

    Cited by:

    1. Lee G. Cooper & Penny Baron & Wayne Levy & Michael Swisher & Paris Gogos, 1999. "PromoCast™: A New Forecasting Method for Promotion Planning," Marketing Science, INFORMS, vol. 18(3), pages 301-316.

  198. Franses, Philip Hans, 1995. "The effects of seasonally adjusting a periodic autoregressive process," Computational Statistics & Data Analysis, Elsevier, vol. 19(6), pages 683-704, June.

    Cited by:

    1. Franses, Philip Hans, 2013. "Data revisions and periodic properties of macroeconomic data," Economics Letters, Elsevier, vol. 120(2), pages 139-141.
    2. Lee G. Cooper & Penny Baron & Wayne Levy & Michael Swisher & Paris Gogos, 1999. "PromoCast™: A New Forecasting Method for Promotion Planning," Marketing Science, INFORMS, vol. 18(3), pages 301-316.
    3. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    4. So, Mike K.P. & Chung, Ray S.W., 2014. "Dynamic seasonality in time series," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 212-226.
    5. Evren Erdoğan Cosar, 2006. "Seasonal behaviour of the consumer price index of Turkey," Applied Economics Letters, Taylor & Francis Journals, vol. 13(7), pages 449-455.

  199. Peter Boswijk, H. & Franses, Philip Hans, 1995. "Testing for periodic integration," Economics Letters, Elsevier, vol. 48(3-4), pages 241-248, June.

    Cited by:

    1. Bensalma, Ahmed, 2018. "Two Distinct Seasonally Fractionally Differenced Periodic Processes," MPRA Paper 84969, University Library of Munich, Germany.
    2. Bohl, Martin T., 2000. "Nonstationary stochastic seasonality and the German M2 money demand function," European Economic Review, Elsevier, vol. 44(1), pages 61-70, January.
    3. Hansen, Hermann-Josef, 1996. "Der Einfluß der Zinsen auf den privaten Verbrauch in Deutschland," Discussion Paper Series 1: Economic Studies 1996,03, Deutsche Bundesbank.
    4. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
    5. Franses, Philip Hans & Paap, Richard, 1995. "Moving average filters and periodic integration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 245-249.
    6. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    7. Hansen, Hermann-Josef, 1996. "The impact of interest rates on private consumption in Germany," Discussion Paper Series 1: Economic Studies 1996,03e, Deutsche Bundesbank.
    8. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    9. Abdelhakim Aknouche & Bader Almohaimeed & Stefanos Dimitrakopoulos, 2022. "Periodic autoregressive conditional duration," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 5-29, January.
    10. Tomás Barrio & Mariam Camarero & Cecilio Tamarit, 2019. "Testing for Periodic Integration with a Changing Mean," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 45-75, June.

  200. Philip Hans Franses, 1995. "IGARCH and variance change in the US long-run interest rate," Applied Economics Letters, Taylor & Francis Journals, vol. 2(4), pages 113-114.

    Cited by:

    1. Amado Peir, 2016. "Changes in the Unconditional Variance and Autoregressive Conditional Heteroscedasticity," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1338-1343.
    2. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    3. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    4. Cathy Yi-Hsuan Chen & Thomas C. Chiang, 2017. "Surprises, sentiments, and the expectations hypothesis of the term structure of interest rates," Review of Quantitative Finance and Accounting, Springer, vol. 49(1), pages 1-28, July.
    5. Guglielmo Maria Caporale & Nikitas Pittis & Nicola Spagnolo, 2003. "IGARCH models and structural breaks," Applied Economics Letters, Taylor & Francis Journals, vol. 10(12), pages 765-768.
    6. Jensen Anders Tolver & Lange Theis, 2010. "On Convergence of the QMLE for Misspecified GARCH Models," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-31, June.
    7. Leonardo Chaves Borges Cardoso & Maurício Vaz Lobo Bittencourt, 2016. "Price Volatility Transmission From Oil To Energy And Non-Energy Agricultural Commodities," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 181, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    8. Ekaterini Tsouma, 2007. "Stock return dynamics and stock market interdependencies," Applied Financial Economics, Taylor & Francis Journals, vol. 17(10), pages 805-825.

  201. Philip Hans Franses & Teun Kloek, 1995. "A periodic cointegration model of quarterly consumption," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 11(2), pages 159-166, June.

    Cited by:

    1. del Barrio Castro, Tomás & Osborn, Denise R., 2008. "Cointegration For Periodically Integrated Processes," Econometric Theory, Cambridge University Press, vol. 24(1), pages 109-142, February.
    2. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
    3. Herwartz, Helmut, 1997. "Performance of periodic error correction models in forecasting consumption data," International Journal of Forecasting, Elsevier, vol. 13(3), pages 421-431, September.

  202. Boswijk, H Peter & Franses, Philip Hans, 1995. "Periodic Cointegration: Representation and Inference," The Review of Economics and Statistics, MIT Press, vol. 77(3), pages 436-454, August.

    Cited by:

    1. del Barrio Castro, Tomás & Osborn, Denise R., 2008. "Cointegration For Periodically Integrated Processes," Econometric Theory, Cambridge University Press, vol. 24(1), pages 109-142, February.
    2. Novales, Alfonso & de Fruto, Rafael Flores, 1997. "Forecasting with periodic models A comparison with time invariant coefficient models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 393-405, September.
    3. Younes Ben Zaied & Marie-Estelle Binet, 2015. "Modelling seasonality in residential water demand: the case of Tunisia," Post-Print halshs-01102007, HAL.
    4. Tomas Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2015. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Empirical Economics, Springer, vol. 49(2), pages 389-402, September.
    5. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    6. Dr. Godwin Chukwudum Nwaobi, 2004. "Modelling Economic Fluctuations In Subsaharan Africa:A Vector Autoregressive Approach," Macroeconomics 0406008, University Library of Munich, Germany.
    7. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "The trade balance in euro countries: a natural case study of periodic integration with a changing mean," Working Papers 1321, Department of Applied Economics II, Universidad de Valencia.
    8. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Bohl, Martin T., 2000. "Nonstationary stochastic seasonality and the German M2 money demand function," European Economic Review, Elsevier, vol. 44(1), pages 61-70, January.
    10. Mårten Löf & Johan Lyhagen, 2003. "On seasonal error correction when the processes include different numbers of unit roots," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 377-389.
    11. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.
    12. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
    13. Evans, Mark, 2006. "A study of the relationship between regional ferrous scrap prices in the USA, 1958-2004," Resources Policy, Elsevier, vol. 31(2), pages 65-77, June.
    14. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    15. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    16. Herwartz, Helmut, 1997. "Performance of periodic error correction models in forecasting consumption data," International Journal of Forecasting, Elsevier, vol. 13(3), pages 421-431, September.
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    1. del Barrio Castro, Tomás & Osborn, Denise R., 2008. "Cointegration For Periodically Integrated Processes," Econometric Theory, Cambridge University Press, vol. 24(1), pages 109-142, February.
    2. Sandro Sapio, 2004. "Market Design, Bidding Rules, and Long Memory in Electricity Prices," LEM Papers Series 2004/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Novales, Alfonso & de Fruto, Rafael Flores, 1997. "Forecasting with periodic models A comparison with time invariant coefficient models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 393-405, September.
    4. Franses, P.H. & Boswijk, H.P., 1993. "Temporal aggregation in a periodically integrated autoregressive process," Other publications TiSEM 2ef3689d-9fa6-419a-850e-5, Tilburg University, School of Economics and Management.
    5. Richard J. Smith & A. M. Robert Taylor & Tomas del Barrio Castro, 2007. "Regression-based seasonal unit root tests," Discussion Papers 07/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    6. Politis, Dimitris, 2016. "HEGY test under seasonal heterogeneity," University of California at San Diego, Economics Working Paper Series qt2q4054kf, Department of Economics, UC San Diego.
    7. Sujata Kar, 2010. "A Periodic Autoregressive Model of Indian WPI Inflation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(3), pages 279-292, August.
    8. Tomas Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2015. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Empirical Economics, Springer, vol. 49(2), pages 389-402, September.
    9. Rodrigues, Paulo M. M. & Taylor, A. M. Robert, 2004. "Alternative estimators and unit root tests for seasonal autoregressive processes," Journal of Econometrics, Elsevier, vol. 120(1), pages 35-73, May.
    10. Rotger, G.P. & Franses, Ph.H.B.F., 2006. "Forecasting high-frequency electricity demand with a diffusion index model," Econometric Institute Research Papers EI 2006-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. John Wells, 1999. "Seasonality, leading indicators, and alternative business cycle theories," Applied Economics, Taylor & Francis Journals, vol. 31(5), pages 531-538.
    12. Tomás del Barrio Castro & Gianluca Cubadda & Denise R. Osborn, 2022. "On cointegration for processes integrated at different frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 412-435, May.
    13. Bradley Michael D. & Jansen Dennis W., 2000. "Are Business Cycle Dynamics the Same across Countries? Testing Linearity around the Globe," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(2), pages 1-23, July.
    14. Kavussanos, Manolis G. & Alizadeh-M, Amir H., 2002. "Seasonality patterns in tanker spot freight rate markets," Economic Modelling, Elsevier, vol. 19(5), pages 747-782, November.
    15. Alexander Vosseler & Enzo Weber, 2017. "Bayesian analysis of periodic unit roots in the presence of a break," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3841-3862, August.
    16. Alexander Vosseler & Enzo Weber, 2018. "Forecasting seasonal time series data: a Bayesian model averaging approach," Computational Statistics, Springer, vol. 33(4), pages 1733-1765, December.
    17. Bentarzi, Mohamed, 1998. "Model-Building Problem of Periodically Correlatedm-Variate Moving Average Processes," Journal of Multivariate Analysis, Elsevier, vol. 66(1), pages 1-21, July.
    18. Franses, Philip Hans & Paap, Richard, 1995. "Moving average filters and periodic integration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 245-249.
    19. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    20. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    21. Franses, Ph.H.B.F. & Paap, R., 2005. "Random-Coefficient periodic autoregression," Econometric Institute Research Papers EI 2005-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    23. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    24. Zacharias Psaradakis, 1996. "Testing for Unit Roots in Time Series with Nearly Deterministic Seasonal Variation," Archive Discussion Papers 9602, Birkbeck, Department of Economics, Mathematics & Statistics.
    25. McElroy Tucker, 2021. "A Diagnostic for Seasonality Based Upon Polynomial Roots of ARMA Models," Journal of Official Statistics, Sciendo, vol. 37(2), pages 367-394, June.
    26. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    27. Shin, Dong Wan & So, Beong Soo, 2000. "Gaussian tests for seasonal unit roots based on Cauchy estimation and recursive mean adjustments," Journal of Econometrics, Elsevier, vol. 99(1), pages 107-137, November.
    28. Evans, Mark, 2006. "A study of the relationship between regional ferrous scrap prices in the USA, 1958-2004," Resources Policy, Elsevier, vol. 31(2), pages 65-77, June.
    29. Mr. Francis Y Kumah, 2006. "The Role of Seasonality and Monetary Policy in Inflation Forecasting," IMF Working Papers 2006/175, International Monetary Fund.
    30. Paulo M.M. Rodrigues & Pedro M.D.C.B. Gouveia, 2004. "An Application of PAR Models for Tourism Forecasting," Tourism Economics, , vol. 10(3), pages 281-303, September.
    31. Granger, E.J. & Swanson, N.R., 1996. "An introduction to stochastic Unit Root Processes," Papers 4-96-3, Pennsylvania State - Department of Economics.
    32. Tucker McElroy & Anindya Roy, 2022. "A Review of Seasonal Adjustment Diagnostics," International Statistical Review, International Statistical Institute, vol. 90(2), pages 259-284, August.
    33. Evren Erdoğan Cosar, 2006. "Seasonal behaviour of the consumer price index of Turkey," Applied Economics Letters, Taylor & Francis Journals, vol. 13(7), pages 449-455.
    34. Franses, Philip Hans & Hylleberg, Svend & Lee, Hahn S., 1995. "Spurious deterministic seasonality," Economics Letters, Elsevier, vol. 48(3-4), pages 249-256, June.
    35. Kunst, Robert M., 2009. "A Nonparametric Test for Seasonal Unit Roots," Economics Series 233, Institute for Advanced Studies.
    36. del Barrio Castro Tomás & Osborn Denise R, 2011. "Nonparametric Tests for Periodic Integration," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-35, February.
    37. Chen Baoline & McElroy Tucker S. & Pang Osbert C., 2022. "Assessing Residual Seasonality in the U.S. National Income and Product Accounts Aggregates," Journal of Official Statistics, Sciendo, vol. 38(2), pages 399-428, June.
    38. Jiajie Kong & Robert Lund, 2023. "Seasonal count time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 93-124, January.
    39. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    40. Md. Samiul Basir & Samuel Noel & Dennis Buckmaster & Muhammad Ashik-E-Rabbani, 2024. "Enhancing Subsurface Soil Moisture Forecasting: A Long Short-Term Memory Network Model Using Weather Data," Agriculture, MDPI, vol. 14(3), pages 1-24, February.
    41. Niels Haldrup & Svend Hylleberg & Gabriel Pons & Jaume Rosselló & Andreu Sansó, 2005. "Common Periodic Correlation Features and the Interaction of Stocks and Flows in Daily Airport Data," Economics Working Papers 2005-03, Department of Economics and Business Economics, Aarhus University.
    42. Tomás Barrio & Mariam Camarero & Cecilio Tamarit, 2019. "Testing for Periodic Integration with a Changing Mean," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 45-75, June.
    43. Peter Boswijk, H. & Franses, Philip Hans, 1995. "Testing for periodic integration," Economics Letters, Elsevier, vol. 48(3-4), pages 241-248, June.
    44. Justyna Wr'oblewska, 2020. "Bayesian analysis of seasonally cointegrated VAR model," Papers 2012.14820, arXiv.org, revised Apr 2021.
    45. Bauer, Dietmar, 2019. "Periodic and seasonal (co-)integration in the state space framework," Economics Letters, Elsevier, vol. 174(C), pages 165-168.
    46. Denise Osborn & Paulo Rodrigues, 2002. "Asymptotic Distributions Of Seasonal Unit Root Tests: A Unifying Approach," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 221-241.
    47. Boswijk, H. Peter & Franses, Philip Hans & Haldrup, Niels, 1997. "Multiple unit roots in periodic autoregression," Journal of Econometrics, Elsevier, vol. 80(1), pages 167-193, September.
    48. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    49. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    50. Polemis, Dionysios & Bentsos, Christos, 2024. "Seasonality patterns in LNG shipping spot and time charter freight rates," Journal of Commodity Markets, Elsevier, vol. 35(C).

  205. Franses, Philip Hans & Paap, Richard, 1994. "Model Selection in Periodic Autoregressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 56(4), pages 421-439, November.

    Cited by:

    1. Novales, Alfonso & de Fruto, Rafael Flores, 1997. "Forecasting with periodic models A comparison with time invariant coefficient models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 393-405, September.
    2. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    3. Tomas Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2015. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Empirical Economics, Springer, vol. 49(2), pages 389-402, September.
    4. Clements, Michael & Smith, Jeremy, 1997. "Forecasting Seasonal UK Consumption Components," The Warwick Economics Research Paper Series (TWERPS) 479, University of Warwick, Department of Economics.
    5. Albertson, Kevin & Aylen, Jonathan, 2003. "Forecasting the behaviour of manufacturing inventory," International Journal of Forecasting, Elsevier, vol. 19(2), pages 299-311.
    6. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.
    8. Franses, Philip Hans & Paap, Richard, 1995. "Moving average filters and periodic integration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 245-249.
    9. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    10. Franses, Ph.H.B.F. & Paap, R., 2005. "Random-Coefficient periodic autoregression," Econometric Institute Research Papers EI 2005-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    12. Albertson, Kevin & Aylen, Jonathan, 1996. "Modelling the Great Lakes freeze: forecasting and seasonality in the market for ferrous scrap," International Journal of Forecasting, Elsevier, vol. 12(3), pages 345-359, September.
    13. Evans, Mark, 2006. "A study of the relationship between regional ferrous scrap prices in the USA, 1958-2004," Resources Policy, Elsevier, vol. 31(2), pages 65-77, June.
    14. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    15. T. Manouchehri & A. R. Nematollahi, 2019. "Periodic autoregressive models with closed skew-normal innovations," Computational Statistics, Springer, vol. 34(3), pages 1183-1213, September.
    16. Herwartz, Helmut, 1997. "Performance of periodic error correction models in forecasting consumption data," International Journal of Forecasting, Elsevier, vol. 13(3), pages 421-431, September.
    17. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    18. Sarnaglia, A.J.Q. & Reisen, V.A. & Lévy-Leduc, C., 2010. "Robust estimation of periodic autoregressive processes in the presence of additive outliers," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2168-2183, October.
    19. Franses, Philip Hans & McAleer, Michael, 1997. "Testing periodically integrated autoregressive models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 457-465.
    20. Franses, Philip Hans & Ooms, Marius, 1997. "A periodic long-memory model for quarterly UK inflation," International Journal of Forecasting, Elsevier, vol. 13(1), pages 117-126, March.
    21. Boswijk, H. Peter & Franses, Philip Hans & Haldrup, Niels, 1997. "Multiple unit roots in periodic autoregression," Journal of Econometrics, Elsevier, vol. 80(1), pages 167-193, September.

  206. Franses, Philip Hans, 1993. "A method to select between periodic cointegration and seasonal cointegration," Economics Letters, Elsevier, vol. 41(1), pages 7-10.

    Cited by:

    1. del Barrio Castro, Tomás & Osborn, Denise R., 2008. "Cointegration For Periodically Integrated Processes," Econometric Theory, Cambridge University Press, vol. 24(1), pages 109-142, February.
    2. Younes Ben Zaied & Marie-Estelle Binet, 2015. "Modelling seasonality in residential water demand: the case of Tunisia," Post-Print halshs-01102007, HAL.
    3. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.

  207. Hans Franses, Philip & Romijn, Gerbert, 1993. "Periodic integration in quarterly UK macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 9(4), pages 467-476, December.

    Cited by:

    1. Novales, Alfonso & de Fruto, Rafael Flores, 1997. "Forecasting with periodic models A comparison with time invariant coefficient models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 393-405, September.
    2. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
    3. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    4. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    5. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    6. Sajjad Akhtar, 2003. "Is There Seasonality in Pakistan’s Merchandise Exports and Imports? The Univariate Modelling Approach," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 42(1), pages 59-75.
    7. Boswijk, H. Peter & Franses, Philip Hans & Haldrup, Niels, 1997. "Multiple unit roots in periodic autoregression," Journal of Econometrics, Elsevier, vol. 80(1), pages 167-193, September.
    8. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    9. Taylor, James W., 2006. "Density forecasting for the efficient balancing of the generation and consumption of electricity," International Journal of Forecasting, Elsevier, vol. 22(4), pages 707-724.

  208. Franses, Philip Hans, 1993. "A model selection procedure for time series with seasonality," Statistics & Probability Letters, Elsevier, vol. 16(4), pages 253-258, March.

    Cited by:

    1. Muhammad Surajo Sanusi & Farooq Ahmad, 2016. "An analysis of seasonality fluctuations in the oil and gas stock returns," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1128133-112, December.

  209. Franses, Philip Hans, 1992. "A model selection test for an AR (1) versus an MA (1) model," Statistics & Probability Letters, Elsevier, vol. 15(4), pages 281-284, November.

    Cited by:

    1. Mckensi, C.R. & Mcaleer, M. & Gill, L., 1990. "Simple Procedures For Testing Autoregressive Versus Moving Average Errors In Regression Models," Papers 210, Australian National University - Department of Economics.
    2. C. R. McKenzie & Michael McAleer, 2001. "Comparing Tests of Autoregressive Versus Moving Average Errors in Regression Models Using Bahadur's Asymptotic Relative Efficiency," ISER Discussion Paper 0537, Institute of Social and Economic Research, Osaka University.

  210. Boswijk, Peter & Franses, Philip Hans, 1992. "Dynamic Specification and Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 369-381, August.

    Cited by:

    1. Beine, Michel & Hecq, Alain, 1998. "Codependence and Convergence in the EC Economies," Journal of Policy Modeling, Elsevier, vol. 20(4), pages 403-426, August.
    2. Chandran Govindaraju, V.G.R. & Tang, Chor Foon, 2013. "The dynamic links between CO2 emissions, economic growth and coal consumption in China and India," Applied Energy, Elsevier, vol. 104(C), pages 310-318.
    3. Schindler, Felix & Voronkova, Svitlana, 2010. "Linkages between international securitized real estate markets: Further evidence from time-varying and stochastic cointegration," ZEW Discussion Papers 10-051, ZEW - Leibniz Centre for European Economic Research.
    4. Barry Falk & Chun-Hsuan Wang, 2003. "Testing long-run PPP with infinite-variance returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 471-484.
    5. Vendrik, M.C.M. & Cörvers, F., 2009. "Male and female labour force participation: The role of dynamic adjustments to changes in labour demand, government policies and autonomous trends," ROA Research Memorandum 013, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    6. Antoine Parent & Christophe Rault, 2005. "The Influences Affecting French Assets Abroad Prior 1914," Documents de recherche 05-14, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    7. Hassink, W.H.J. & Broersma, L., 1993. "Labour demand and job-to-job movement : macro-consequences as a result from micro-economic behaviour," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. Moonsoo Park & Yanhong H. Jin & David A. Bessler, 2008. "The impacts of animal disease crises on the Korean meat market," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 183-195, September.
    9. Jude Okechukwu Chukwu, 2013. "Budget Deficits, Money Growth and Price Level in Nigeria," African Development Review, African Development Bank, vol. 25(4), pages 468-477.
    10. Baharumshah, Ahmad Zubaidi & M. Masih, A. Mansur & Azali, M., 2002. "The stock market and the ringgit exchange rate: a note," Japan and the World Economy, Elsevier, vol. 14(4), pages 471-486, December.
    11. Andersson, Michael K. & Gredenhoff, Mikael P., 1999. "On the maximum likelihood cointegration procedure under a fractional equilibrium error," Economics Letters, Elsevier, vol. 65(2), pages 143-147, November.
    12. Haug, Alfred A., 1996. "Tests for cointegration a Monte Carlo comparison," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 89-115.
    13. Urbain, Jean-Pierre, 1995. "Partial versus full system modelling of cointegrated systems an empirical illustration," Journal of Econometrics, Elsevier, vol. 69(1), pages 177-210, September.
    14. El-Sakka M. I. T. & Ghali Khalifa H, 2005. "The Sources of Inflation in Egypt: A Multivariate Co-integration Analysis," Review of Middle East Economics and Finance, De Gruyter, vol. 3(3), pages 84-96, December.
    15. H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2022. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Papers 2202.02532, arXiv.org.
    16. Pesavento, Elena, 2000. "Analytical Evaluation of the Power of Tests for the Absence of Cointegration," University of California at San Diego, Economics Working Paper Series qt4cq4773c, Department of Economics, UC San Diego.
    17. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    18. Österholm, Pär, 2003. "Testing for Cointegration in Misspecified Systems –A Monte Carlo Study of Size Distortions," Working Paper Series 2003:21, Uppsala University, Department of Economics.
    19. Doyle, Matthew & Falk, Barry L., 2004. "Testing Commitment Models of Monetary Policy: Evidence from OECD Economies," Staff General Research Papers Archive 11995, Iowa State University, Department of Economics.
    20. Yannick L'horty & Christophe Rault, 2003. "Why Is French Equilibrium Unemployment So High?," Journal of Applied Economics, Universidad del CEMA, vol. 6, pages 127-156, May.
    21. Yannick L'horty & Christophe Rault, 2003. "Why Is French Equilibrium Unemployment So High? an Estimation of the Ws-Ps Model," Journal of Applied Economics, Taylor & Francis Journals, vol. 6(1), pages 127-156, May.
    22. Kevin S. Nell, 1999. "The Endogenous/Exogenous Nature of South Africa's Money Supply Under Direct and Indirect Monetary Control Measures," Studies in Economics 9912, School of Economics, University of Kent.
    23. J.P.A. Sagaram & J. Wickramanayake, 2005. "Financial centers in the Asia-pacific region: an empirical study on australia, Hong Kong, Japan and Singapore," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 21-51.
    24. Jose Manuel Gonzalez-Paramo, 1995. "Infraestructuras, productividad y bienestar," Investigaciones Economicas, Fundación SEPI, vol. 19(1), pages 155-168, January.
    25. Mototsugu Shintani, 2000. "A Simple Cointegrating Rank Test Without Vector Autoregression," Vanderbilt University Department of Economics Working Papers 0044, Vanderbilt University Department of Economics.
    26. Christian Kascha & Carsten Trenkler, 2009. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Working Paper 2009/12, Norges Bank.
    27. Farhani, Sahbi & Solarin, Sakiru Adebola, 2017. "Financial development and energy demand in the United States: New evidence from combined cointegration and asymmetric causality tests," Energy, Elsevier, vol. 134(C), pages 1029-1037.
    28. Murthy, N. R. Vasudeva & Phillips, Joseph M., 1996. "The relationship between budget deficits and capital inflows: Further econometric evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(4), pages 485-494.
    29. Rashid, Shahidur, 2002. "Dynamics of agricultural wage and rice price in Bangladesh," MTID discussion papers 44, International Food Policy Research Institute (IFPRI).
    30. Badi H. Baltagi & Zijun Wang, 2006. "Testing for Cointegrating Rank via Model Selection: Evidence from 165 Data Sets," Center for Policy Research Working Papers 83, Center for Policy Research, Maxwell School, Syracuse University.
    31. Dorosh, Paul A. & Rashid, Shahidur, 2012. "Bangladesh rice trade and price stabilization: Implications of the 2007/08 experience for public stocks," IFPRI discussion papers 1209, International Food Policy Research Institute (IFPRI).
    32. Judith A. Giles & Sadaf Mirza, 1999. "Some Pretesting Issues on Testing for Granger Noncausality," Econometrics Working Papers 9914, Department of Economics, University of Victoria.
    33. Allan W. Gregory & Alfred A. Haug & Nicoletta Lomuto, 2004. "Mixed signals among tests for cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 89-98.
    34. David Aristei & Luca Pieroni, 2005. "Estimating the Role of Government Expenditure in Long-run Consumption," Quaderni del Dipartimento di Economia, Finanza e Statistica 13/2005, Università di Perugia, Dipartimento Economia.
    35. Holtedahl, Pernille & Joutz, Frederick L., 2004. "Residential electricity demand in Taiwan," Energy Economics, Elsevier, vol. 26(2), pages 201-224, March.
    36. Dorosh, Paul A. & Rashid, Shahidur, 2013. "Trade subsidies, export bans and price stabilization: Lessons of Bangladesh–India rice trade in the 2000s," Food Policy, Elsevier, vol. 41(C), pages 103-111.
    37. Jing Li & Junsoo Lee, 2010. "ADL tests for threshold cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 241-254, July.
    38. Ho, Mun S & Sorensen, Bent E, 1996. "Finding Cointegration Rank in High Dimensional Systems Using the Johansen Test: An Illustration Using Data Based Monte Carlo Simulations," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 726-732, November.

  211. Franses, Philip Hans, 1992. "The Norwegian Consumption Function: A Comment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 455-459, August.

    Cited by:

    1. Eitrheim,O. & Jansen,E.S. & Nymoen,R., 2000. "Progress from forecast failure : the Norwegian consumption function," Memorandum 32/2000, Oslo University, Department of Economics.

  212. Franses, Philip Hans, 1992. "Modeling seasonality in bimonthly time series," Statistics & Probability Letters, Elsevier, vol. 15(5), pages 407-415, December.

    Cited by:

    1. Shin, Dong Wan & So, Beong Soo, 2000. "Gaussian tests for seasonal unit roots based on Cauchy estimation and recursive mean adjustments," Journal of Econometrics, Elsevier, vol. 99(1), pages 107-137, November.

  213. Hans Franses, Philip, 1992. "Testing for seasonality," Economics Letters, Elsevier, vol. 38(3), pages 259-262, March.

    Cited by:

    1. Ghysels, E., 1993. "A Time Series Model with Periodic Stochastic Regime Switching," Cahiers de recherche 9314, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Webel, Karsten, 2016. "A data-driven selection of an appropriate seasonal adjustment approach," Discussion Papers 07/2016, Deutsche Bundesbank.
    3. Ollech, Daniel & Webel, Karsten, 2020. "A random forest-based approach to identifying the most informative seasonality tests," Discussion Papers 55/2020, Deutsche Bundesbank.
    4. OUERFELLI, Chokri, 1998. "La demande touristique européenne en Tunisie," LATEC - Document de travail - Economie (1991-2003) 1998-14, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.

  214. Franses, Philip Hans, 1991. "Moving average filters and unit roots," Economics Letters, Elsevier, vol. 37(4), pages 399-403, December.

    Cited by:

    1. Fabio Busetti, 2004. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Econometrics 0411003, University Library of Munich, Germany.
    2. Chouhan, Rajesh & Dhamaniya, Ashish & Antoniou, Constantinos, 2024. "Analysis of driving behavior in weak lane disciplined traffic at the merging and diverging sections using unmanned aerial vehicle data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 646(C).
    3. Josef Arlt, 2023. "The problem of annual inflation rate indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2772-2788, July.
    4. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
    5. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    6. Rodrigues, Paulo M. M., 2000. "A note on the application of the DF test to seasonal data," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 171-175, April.
    7. Hassler Uwe & Demetrescu Matei, 2005. "Spurious Persistence and Unit Roots due to Seasonal Differencing: The Case of Inflation Rates / Künstliche Persistenz und Einheitswurzeln infolge saisonaler Differenzen: Das Beispiel Inflationsraten," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(4), pages 413-426, August.

  215. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
    See citations under working paper version above.
  216. Philip Hans Franses & Paul Kofman, 1991. "An empirical test for parities between metal prices at the LME," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(6), pages 729-736, December.
    See citations under working paper version above.

Chapters

  1. Philip Hans Franses & Dick Dijk, 2011. "GARCH, Outliers, and Forecasting Volatility," Palgrave Macmillan Books, in: Greg N. Gregoriou & Razvan Pascalau (ed.), Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models, chapter 8, pages 136-159, Palgrave Macmillan.

    Cited by:

    1. Francq, Christian & Zakoian, Jean-Michel, 2019. "Testing the existence of moments for GARCH processes," MPRA Paper 98892, University Library of Munich, Germany.

  2. Philip Hans Franses, 2008. "Forecasting Seasonal Time Series," World Scientific Book Chapters, in: Roberto S Mariano & Yiu-Kuen Tse (ed.), Econometric Forecasting And High-Frequency Data Analysis, chapter 3, pages 93-130, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1109, Universitá degli Studi di Milano.

  3. Marnik G. Dekimpe & Philip Hans Franses & Dominique M. Hanssens & Prasad A. Naik, 2008. "Time-Series Models in Marketing," International Series in Operations Research & Management Science, in: Berend Wierenga (ed.), Handbook of Marketing Decision Models, chapter 0, pages 373-398, Springer.
    • Dekimpe, M.G. & Franses, Ph.H.B.F. & Hanssens, D.M. & Naik, P., 2006. "Time-Series Models in Marketing," ERIM Report Series Research in Management ERS-2006-049-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    See citations under working paper version above.
  4. Franses, Philip Hans, 2006. "Forecasting in Marketing," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 18, pages 983-1012, Elsevier.
    See citations under working paper version above.
  5. Christian M. Hafner & Dick van Dijk & Philip Hans Franses, 2006. "Semi-Parametric Modelling of Correlation Dynamics," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 59-103, Emerald Group Publishing Limited.
    See citations under working paper version above.

Books

  1. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.

    Cited by:

    1. Bartosz Kozicki & Grzegorz Mizura & Artur Stopka & Mateusz Andrzej Jędryka, 2021. "Metodyka planowania potrzeb finansowych z wykorzystaniem prognozowania danych retrospektywnych w aspekcie bezpieczeństwa ekonomicznego," Nowoczesne Systemy Zarządzania. Modern Management Systems, Military University of Technology, Faculty of Security, Logistics and Management, Institute of Organization and Management, issue 4, pages 95-108.
    2. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Andreea MIRICĂ & Tudorel ANDREI & Elena-Doina DASCĂLU & George-Ioan MINCU RĂDULESCU & Ionela-Roxana GLĂVA, 2016. "Revision Policy Of Seasonally Adjusted Series – Case Study On Romanian Quarterly Gdp," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 45-62.
    4. Mutele, Litshedzani & Carranza, Emmanuel John M., 2024. "Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Afr," Resources Policy, Elsevier, vol. 93(C).
    5. Philip Hans Franses, 2020. "IMA(1,1) as a new benchmark for forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 27(17), pages 1419-1423, October.
    6. Philip Hans Franses, 2018. "Prediction Intervals For Expert-Adjusted Forecasts," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 308-320, December.
    7. Franses, Ph.H.B.F., 2019. "Estimating persistence for irregularly spaced historical data," Econometric Institute Research Papers EI2020-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Stefanescu, Răzvan & Dumitriu, Ramona, 2019. "Obiective ale analizei trendurilor seriilor de timp discrete [Objectives of the analysis of trends in discrete time series]," MPRA Paper 97821, University Library of Munich, Germany, revised 23 Dec 2019.
    9. Marco Rubilar-González & Gabriel Pino, 2018. "Are Euro-Area expectations about recession phases effective to anticipate consequences of economic crises?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 141-161, June.
    10. Adriana Scrioșteanu & Maria Magdalena Criveanu, 2023. "Reverse Logistics of Packaging Waste under the Conditions of a Sustainable Circular Economy at the Level of the European Union States," Sustainability, MDPI, vol. 15(20), pages 1-15, October.
    11. Claire Y. T. Chen & Edward W. Sun & Ming-Feng Chang & Yi-Bing Lin, 2024. "Enhancing travel time prediction with deep learning on chronological and retrospective time order information of big traffic data," Annals of Operations Research, Springer, vol. 343(3), pages 1095-1128, December.
    12. Adriana Scrioșteanu & Maria Magdalena Criveanu, 2024. "Green and Reserve Logistics of Packaging and Plastic Packaging Waste under the Conditions of Circular Economy at the Level of the European Union Member States," Energies, MDPI, vol. 17(12), pages 1-19, June.

  2. Franses,Philip Hans, 2014. "Expert Adjustments of Model Forecasts," Cambridge Books, Cambridge University Press, number 9781107081598, January.

    Cited by:

    1. Franses, Ph.H.B.F. & de Bruijn, L.P., 2015. "Benchmarking judgmentally adjusted forecasts," Econometric Institute Research Papers EI2015-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    4. Philip Hans Franses, 2019. "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(2), pages 73-80, March.
    5. Philip Hans Franses, 2024. "Incorporating judgment in forecasting models in times of crisis," Futures & Foresight Science, John Wiley & Sons, vol. 6(4), December.
    6. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
    7. Franses, Ph.H.B.F. & Welz, M., 2018. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Econometric Institute Research Papers EI2018-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Fildes, Robert & Goodwin, Paul & Önkal, Dilek, 2019. "Use and misuse of information in supply chain forecasting of promotion effects," International Journal of Forecasting, Elsevier, vol. 35(1), pages 144-156.
    9. Philip Hans Franses, 2018. "Prediction Intervals For Expert-Adjusted Forecasts," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 308-320, December.
    10. Petropoulos, Fotios & Goodwin, Paul & Fildes, Robert, 2017. "Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge," International Journal of Forecasting, Elsevier, vol. 33(1), pages 314-324.
    11. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.
    12. Philip Hans Franses & Max Welz, 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," JRFM, MDPI, vol. 13(3), pages 1-8, March.
    13. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Philip Hans Franses, 2021. "Testing bias in professional forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1086-1094, September.

  3. Franses,Philip Hans & Paap,Richard, 2010. "Quantitative Models in Marketing Research," Cambridge Books, Cambridge University Press, number 9780521143653, January.

    Cited by:

    1. Ginés Guirao Pérez & Victor Javier Cano Fernández & Marta Isabel López Yurda & María Carolina Rodríguez Donate & Margarita Esther Romero Rodríguez, 2004. "Relación entre la frecuencia de consumo de vino y algunas características socioeconómicas de los individuos," Documentos de trabajo conjunto ULL-ULPGC 2004-01, Facultad de Ciencias Económicas de la ULPGC.
    2. Maruyama, Masayoshi & Flath, David & Minamikawa, Kazumitsu & Ohkita, Kenichi & Zennyo, Yusuke, 2015. "Platform selection by software developers: Theory and evidence," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 282-303.
    3. Heij, C. & Franses, Ph.H.B.F., 2010. "Correcting for Survey Effects in Pre-election Polls," Econometric Institute Research Papers EI 2010-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Segers, Rene & Franses, Philip Hans & de Bruijn, Bert, 2017. "A novel approach to measuring consumer confidence," Econometrics and Statistics, Elsevier, vol. 4(C), pages 121-129.
    5. Risselada, Hans & Verhoef, Peter C. & Bijmolt, Tammo H.A., 2010. "Staying Power of Churn Prediction Models," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 198-208.
    6. Zewei Lin & Dungang Liu, 2022. "Model diagnostics of discrete data regression: a unifying framework using functional residuals," Papers 2207.04299, arXiv.org.
    7. Chan, Moon-tong & Yu, Dalei & Yau, Kelvin K.W., 2015. "Multilevel cumulative logistic regression model with random effects: Application to British social attitudes panel survey data," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 173-186.
    8. Yabing Jiang & Hong Guo, 2015. "Design of Consumer Review Systems and Product Pricing," Information Systems Research, INFORMS, vol. 26(4), pages 714-730, December.
    9. Els Breugelmans & Yuping Liu-Thompkins, 2017. "The effect of loyalty program expiration policy on consumer behavior," Marketing Letters, Springer, vol. 28(4), pages 537-550, December.
    10. Franses, Ph.H.B.F., 2004. "Forecasting in marketing," Econometric Institute Research Papers EI 2004-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Kremer, Sara T.M. & Bijmolt, Tammo H.A. & Leeflang, Peter S.H. & Wieringa, Jaap E., 2008. "Generalizations on the effectiveness of pharmaceutical promotional expenditures," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 234-246.
    12. Potharst, R. & van Rijthoven, M. & van Wezel, M.C., 2005. "Modeling brand choice using boosted and stacked neural networks," Econometric Institute Research Papers EI 2005-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Dekimpe, M.G. & Hanssens, D.M. & Nijs, V.R. & Steenkamp, J-B.E.M., 2003. "Measuring Short- and Long-run Promotional Effectiveness on Scanner Data Using Persistence Modeling," ERIM Report Series Research in Management ERS-2003-087-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. van Wezel, Michiel & Potharst, Rob, 2007. "Improved customer choice predictions using ensemble methods," European Journal of Operational Research, Elsevier, vol. 181(1), pages 436-452, August.
    15. Dennis Fok & Richard Paap, 2009. "Modeling category‐level purchase timing with brand‐level marketing variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 469-489, April.
    16. Makoto Abe, 2006. ""Counting Your Customers" One by One: An Individual Level RF Analysis Based on Consumer Behavior Theory," CIRJE F-Series CIRJE-F-408, CIRJE, Faculty of Economics, University of Tokyo.
    17. Richard Paap, 2002. "What are the advantages of MCMC based inference in latent variable models?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(1), pages 2-22, February.
    18. Franses, Ph.H.B.F. & Patoir, D.A., 2002. "Modeling students' evealuation scores; comparing economics schools in Maastricht and Rotterdam," Econometric Institute Research Papers EI 2002-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Polo, Yolanda & Sese, F. Javier & Verhoef, Peter C., 2011. "The Effect of Pricing and Advertising on Customer Retention in a Liberalizing Market," Journal of Interactive Marketing, Elsevier, vol. 25(4), pages 201-214.
    20. Prinz, Aloys & Bünger, Björn, 2009. "The decline of relational goods in the production of well-being?," CAWM Discussion Papers 21, University of Münster, Münster Center for Economic Policy (MEP).
    21. Leenheer, Jorna & Bijmolt, Tammo H.A., 2008. "Which retailers adopt a loyalty program? An empirical study," Journal of Retailing and Consumer Services, Elsevier, vol. 15(6), pages 429-442.
    22. David A. Schweidel & George Knox, 2013. "Incorporating Direct Marketing Activity into Latent Attrition Models," Marketing Science, INFORMS, vol. 32(3), pages 471-487, May.
    23. Mohamed Abdallah Ali & Mazhar Mughal & Charles Kodjo Mawusi, 2021. "Does Khat Consumption Affect Work Performance ? A Micro-Perspective from Djibouti," Working papers of Transitions Energétiques et Environnementales (TREE) hal-03375659, HAL.
    24. van Wezel, M.C. & Potharst, R., 2005. "Improved customer choice predictions using ensemble methods," Econometric Institute Research Papers EI 2005-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    25. Liu, Dungang & Li, Shaobo & Yu, Yan & Moustaki, Irini, 2020. "Assessing partial association between ordinal variables: quantification, visualization, and hypothesis testing," LSE Research Online Documents on Economics 105558, London School of Economics and Political Science, LSE Library.
    26. Edwin Van Gameren & Michiel Ras & Evelien Eggink & Ingrid Ooms, 2005. "The demand for housing services in the Netherlands," ERSA conference papers ersa05p327, European Regional Science Association.
    27. Perez, G. Guirao & Fernandez, V. Cano & Yurda, M.I. Lopez & Donate, M.C. Rodriguez, 2002. "Socioeconomic Factors and the Consumption of Wine in Tenerife," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24798, European Association of Agricultural Economists.
    28. van Nierop, J.E.M. & Leeflang, P.S.H. & Teerling, M.L. & Huizingh, K.R.E., 2011. "The impact of the introduction and use of an informational website on offline customer buying behavior," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 155-165.
    29. Ben Youssef, Adel & Dahmani, Mounir & Omrani, Nessrine, 2012. "Students' e-skills, organizational change and diversity of learning processs: Evidence from French universities in 2010," ZEW Discussion Papers 12-031, ZEW - Leibniz Centre for European Economic Research.
    30. Vicari, Donatella & Alfó, Marco, 2014. "Model based clustering of customer choice data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 3-13.
    31. Qian, Lixian & Soopramanien, Didier & Daryanto, Ahmad, 2017. "First-time buyers' subjective knowledge and the attribute preferences of Chinese car buyers," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 189-196.
    32. Björn Bünger, 2010. "The demand for relational goods: empirical evidence from the European Social Survey," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 57(2), pages 177-198, June.
    33. Lemmens, A. & Croux, C., 2006. "Bagging and boosting classification trees to predict churn," Other publications TiSEM d5cb664d-5859-44db-a621-e, Tilburg University, School of Economics and Management.
    34. Sibdari, Soheil & Pyke, David F., 2010. "A competitive dynamic pricing model when demand is interdependent over time," European Journal of Operational Research, Elsevier, vol. 207(1), pages 330-338, November.
    35. Clarijs, P. & Hogeling, B. & Franses, Ph.H.B.F. & Heij, C., 2007. "Evaluation of survey effects in pre-election polls," Econometric Institute Research Papers EI 2007-50, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    36. Robert Kapłon, 2006. "A retrospective review of categorical data analysis – theory and marketing practice," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(1), pages 55-72.
    37. Christoph Fuchs & Martijn G. de Jong & Martin Schreier, 2020. "Earmarking Donations to Charity: Cross-cultural Evidence on Its Appeal to Donors Across 25 Countries," Management Science, INFORMS, vol. 66(10), pages 4820-4842, October.
    38. Sloot, L.M. & Verhoef, P.C. & Franses, Ph.H.B.F., 2002. "The impact of brand and category characteristics on consumer stock-out reactions," ERIM Report Series Research in Management ERS-2002-106-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    39. Zhao, Li & Tian, Peng & Xiangyong Li, 2012. "Dynamic pricing in the presence of consumer inertia," Omega, Elsevier, vol. 40(2), pages 137-148, April.
    40. Friederike Paetz & Winfried J. Steiner & Harald Hruschka, 2022. "“Advanced data analysis techniques with marketing applications”," Journal of Business Economics, Springer, vol. 92(4), pages 557-561, May.
    41. Philip Hans Franses & Richard Paap, 2025. "Testing for Bias in Forecasts for Independent Multinomial Outcomes," Forecasting, MDPI, vol. 7(1), pages 1-8, January.
    42. Abdelfatah Ichou, 2010. "Modelling the Determinants of Job Creation: Microeconometric Models Accounting for Latent Entrepreneurial Ability," Scales Research Reports H201018, EIM Business and Policy Research.
    43. van Lin, Arjen & Gijsbrechts, Els, 2016. "The battle for health and beauty: What drives supermarket and drugstore category-promotion lifts?," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 557-577.
    44. Heij, C. & Knapp, S., 2018. "Shipping Inspections, Detentions, and Accidents: An Empirical Analysis of Risk Dimensions," Econometric Institute Research Papers 2018-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    45. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics (QME), Springer, vol. 5(2), pages 163-190, June.
    46. Defrancesco, Edi, 2002. "The Beginning Of Organic Fish Farming In Italy," Working Papers 14367, University of Minnesota, Center for International Food and Agricultural Policy.
    47. Peter C. Verhoef & Martin Heijnsbroek & Joost Bosma, 2017. "Developing A Service Improvement System for the National Dutch Railways," Interfaces, INFORMS, vol. 47(6), pages 489-504, December.
    48. Nicole van Nes & Jacqueline Cramer, 2005. "Influencing product lifetime through product design," Business Strategy and the Environment, Wiley Blackwell, vol. 14(5), pages 286-299, September.
    49. Adel Ben Youssef & Mounir Dahmani & Nessrine Omrani, 2013. "Information technologies, students'e-skills and diversity of learning process," Post-Print halshs-00937145, HAL.
    50. de Jong, M.G., 2006. "Response bias in international marketing research," Other publications TiSEM 5d4031be-97b5-4db3-962b-2, Tilburg University, School of Economics and Management.
    51. Segers, R. & Franses, Ph.H.B.F., 2008. "Measuring weekly consumer confidence," Econometric Institute Research Papers EI 2008-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    52. Bioch, J.C. & Groenen, P.J.F. & Nalbantov, G.I., 2005. "Solving and interpreting binary classification problems in marketing with SVMs," Econometric Institute Research Papers EI 2005-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    53. Romina Gambacorta & Maria Iannario, 2012. "Statistical models for measuring job satisfaction," Temi di discussione (Economic working papers) 852, Bank of Italy, Economic Research and International Relations Area.
    54. Vroomen, B.L.K. & Donkers, A.C.D. & Verhoef, P.C. & Franses, Ph.H.B.F., 2003. "Purchasing complex services on the Internet; An analysis of mortgage loan acquisitions," ERIM Report Series Research in Management ERS-2003-075-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    55. Ming Yin & Zheng Wan & Kap Hwan Kim & Shi Yuan Zheng, 2019. "An optimal variable pricing model for container line revenue management systems," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(2), pages 173-191, June.
    56. Heij, C. & Knapp, S., 2014. "Effects of wind strength and wave height on ship incident risk: regional trends and seasonality," Econometric Institute Research Papers EI2014-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    57. Abhijit Sengupta & Stephen E. Glavin, 2010. "Volatility In The Consumer Packaged Goods Industry — A Simulation Based Study," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 579-605.
    58. Zhao, Shangwei & Zhou, Jianhong & Yang, Guangren, 2019. "Averaging estimators for discrete choice by M-fold cross-validation," Economics Letters, Elsevier, vol. 174(C), pages 65-69.
    59. Eoghan O'Neill, 2022. "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression," Papers 2211.07506, arXiv.org, revised Feb 2024.
    60. Lin, Kyle Y. & Sibdari, Soheil Y., 2009. "Dynamic price competition with discrete customer choices," European Journal of Operational Research, Elsevier, vol. 197(3), pages 969-980, September.
    61. Fernández-Durán, J.J., 2016. "Defining generational cohorts for marketing in Mexico," Journal of Business Research, Elsevier, vol. 69(2), pages 435-444.

  4. Franses, Philip Hans & Paap, Richard, 2004. "Periodic Time Series Models," OUP Catalogue, Oxford University Press, number 9780199242030.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Q. Shao, 2008. "Robust Estimation For Periodic Autoregressive Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 251-263, March.
    3. Pawel Maryniak & Rafal Weron, 2014. "Forecasting the occurrence of electricity price spikes in the UK power market," HSC Research Reports HSC/14/11, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    4. Politis, Dimitris, 2016. "HEGY test under seasonal heterogeneity," University of California at San Diego, Economics Working Paper Series qt2q4054kf, Department of Economics, UC San Diego.
    5. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
    6. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series 015, University of Pavia, Department of Economics and Management.
    7. Jin Zou & Dong Han, 2021. "Yule–Walker Equations Using a Gini Covariance Matrix for the High-Dimensional Heavy-Tailed PVAR Model," Mathematics, MDPI, vol. 9(6), pages 1-15, March.
    8. Nicholas J. Cox, 2009. "Stata tip 76: Separating seasonal time series," Stata Journal, StataCorp LP, vol. 9(2), pages 321-326, June.
    9. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    10. Tomas Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2015. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Empirical Economics, Springer, vol. 49(2), pages 389-402, September.
    11. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    12. Pierre Duchesne & Pierre Lafaye de Micheaux, 2013. "Distributions for residual autocovariances in parsimonious periodic vector autoregressive models with applications," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 496-507, July.
    13. Marius Ötting & Roland Langrock & Christian Deutscher & Vianey Leos‐Barajas, 2020. "The hot hand in professional darts," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 565-580, February.
    14. Baek, Changryong & Davis, Richard A. & Pipiras, Vladas, 2017. "Sparse seasonal and periodic vector autoregressive modeling," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 103-126.
    15. Panagiotelis, Anastasios & Smith, Michael, 2010. "Bayesian skew selection for multivariate models," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1824-1839, July.
    16. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    17. Dillon Alleyne, 2006. "Can Seasonal Unit Root Testing Improve the Forecasting Accuracy of Tourist Arrivals?," Tourism Economics, , vol. 12(1), pages 45-64, March.
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    59. Beatriz Rodríguez-Sánchez & Talitha L. Feenstra & Henk J. G. Bilo & Rob. J. M. Alessie, 2019. "Costs of people with diabetes in relation to average glucose control: an empirical approach controlling for year of onset cohorts," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(7), pages 989-1000, September.
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    62. B. Rodriguez-Sanchez & R. J. M. Alessie & T. L. Feenstra & V. Angelini, 2018. "The relationship between diabetes, diabetes-related complications and productive activities among older Europeans," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(5), pages 719-734, June.
    63. Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2009. "Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i03).
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    72. Ghassan, Hassan B. & Guendouz, Abdelkarim, 2018. "Panel Modeling of Z-score: Evidence from Islamic and Conventional Saudi Banks," MPRA Paper 95900, University Library of Munich, Germany, revised 05 Jan 2019.
    73. Malik, Afia, 2018. "Fuel Demand in Pakistan's TRansport Sector," MPRA Paper 103455, University Library of Munich, Germany.
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    75. Odolinski, Kristofer & Boysen, Hans E., 2018. "Railway line capacity utilisation and its impact on maintenance costs," Working papers in Transport Economics 2018:10, CTS - Centre for Transport Studies Stockholm (KTH and VTI), revised 30 Oct 2018.
    76. Johannes Paha, 2011. "Empirical methods in the analysis of collusion," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 38(3), pages 389-415, July.
    77. Osvaldo Lagares, 2016. "Capital, Economic Growth and Relative Income Differences in Latin America," Discussion Papers 16/03, Department of Economics, University of York.
    78. Sugra Ingilab Humbatova & Fariz Saleh Ahmadov & lgar Zulfigar Seyfullayev & Natig Gadim-Ogli Hajiyev, 2020. "The Relationship between Electricity Consumption and Economic Growth: Evidence from Azerbaijan," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 436-455.
    79. Antonio Zoratto Sanvicente & Renato Teles Delgado, 2010. "Learning Theory and Equity Valuation: an Empirical Analysis," Brazilian Review of Finance, Brazilian Society of Finance, vol. 8(2), pages 113-139.
    80. Y. Sekou Bermiss & Edward J. Zajac & Brayden G King, 2014. "Under Construction: How Commensuration and Management Fashion Affect Corporate Reputation Rankings," Organization Science, INFORMS, vol. 25(2), pages 591-608, April.
    81. Laitila, Thomas & Wang, Lisha, 2015. "A Two-Step Estimator for Missing Values in Probit Model Covariates," Working Papers 2015:3, Örebro University, School of Business.
    82. S Arnold, 2010. "Environmental Decision Making and Behaviours: How do People Choose how to Travel to Work?," Department of Economics Working Papers 07/10, University of Bath, Department of Economics.
    83. Marius Ooms & Jurgen A. Doornik, 2006. "Econometric software development: past, present and future," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(2), pages 206-224, May.
    84. Odolinski , Kristofer, 2016. "The impact of cumulative tons on rail infrastructure maintenance costs," Working papers in Transport Economics 2016:28, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    85. Peter, Manuel, 2015. "Konvergenz der europäischen Aktienmärkte: Eine Analyse der Entwicklungen und Herausforderungen für Investoren," Arbeitspapiere 150, University of Münster, Institute for Cooperatives.
    86. La Saidi & Pasrun Adam & Rostin & Zainuddin Saenong & Muh. Yani Balaka & Gamsir & Asmuddin & Salwiah, 2017. "The Effect of Stock Prices and Exchange Rates on Economic Growth in Indonesia," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 527-533.
    87. Tahamina Khanam & Abul Rahman & Blas Mola-Yudego & Jouni Pykäläinen, 2017. "Identification of structural breaks in the forest product markets: how sensitive are to changes in the Nordic region?," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(3), pages 469-483, March.
    88. Juraj Hruška, 2015. "Delta-gamma-theta Hedging of Crude Oil Asian Options," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(6), pages 1897-1903.
    89. Ana Moura & Pedro Pita Barros, 2020. "Entry and price competition in the over‐the‐counter drug market after deregulation: Evidence from Portugal," Health Economics, John Wiley & Sons, Ltd., vol. 29(8), pages 865-877, August.
    90. Knapp, S. & Franses, Ph.H.B.F. & B. Whitby (Bruce), 2020. "Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis," Econometric Institute Research Papers EI 2020-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    91. Ibrahim M. Awad & Abdel-Rahman Al-Ewesat, 2017. "Volatility Persistence in Palestine Exchange Bulls and Bears: An Econometric Analysis of Time Series Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 9, pages 83-97, August.
    92. H. K. Van Dijk & J. F. Kaashoek & A. P. M. Wagelmans, 2006. "‘Rotterdam econometrics’: an analysis of publications of the Econometric Institute 1956–2004," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(2), pages 85-111, May.
    93. Beatriz Rodríguez-Sánchez & Marta Pascual Sáez & David Cantarero-Prieto, 2021. "Dependent, Poorer, and More Care-Demanding? An Analysis of the Relationship between Being Dependent, Household Income, and Formal and Informal Care Use in Spain," IJERPH, MDPI, vol. 18(8), pages 1-17, April.
    94. Christian Calmès & Raymond Théoret, 2023. "Bank performance before and after the subprime crisis: Evidence from pooled data on big US banks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 472-516, June.
    95. Donkor, Emmanuel & Onakuse, Stephen & Bogue, Joe & De Los Rios-Carmenado, Ignacio, 2019. "Fertiliser adoption and sustainable rural livelihood improvement in Nigeria," Land Use Policy, Elsevier, vol. 88(C).
    96. Sif Jónsdóttir & Tinna Ásgeirsdóttir, 2014. "The effect of job loss on body weight during an economic collapse," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(6), pages 567-576, July.
    97. Abd Azis Muthalib & Pasrun Adam & Rostin Rostin & Zainuddin Saenong & La Ode Suriadi, 2018. "The Influence of Fuel Prices and Unemployment Rate towards the Poverty Level in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 37-42.
    98. Narbel, Patrick A. & Isaksen, Elisabeth T., 2014. "A carbon footprint proportional to expenditure - a case for Norway?," Discussion Papers 2014/16, Norwegian School of Economics, Department of Business and Management Science.
    99. Hassouneh, Islam & Serra, Teresa & Goodwin, Barry K. & Gil, José M., 2012. "Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships," Energy Economics, Elsevier, vol. 34(5), pages 1507-1513.
    100. David Cantarero & Marta Pascual & Beatriz Rodríguez-Sánchez, 2022. "Differences in the Use of Formal and Informal Care Services among Older Adults after the Implementation of the Dependency Act in Spain," Hacienda Pública Española / Review of Public Economics, IEF, vol. 240(1), pages 61-93, March.
    101. Richard DeFusco & Stoyu Ivanov & Gordon Karels, 2011. "The exchange traded funds’ pricing deviation: analysis and forecasts," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(2), pages 181-197, April.
    102. Camilo Meyberg & Ulrich Rendtel & Holger Leerhoff, 2024. "Flat rent price prediction in Berlin with web scraping," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 18(2), pages 245-278, June.
    103. Rezitis Anthony N. & Rokopanos Andreas, 2019. "Asymmetric Price Transmission along the European Food Supply Chain and the CAP Health Check: a Panel Vector Error Correction Approach," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 17(2), pages 1-20, November.
    104. Nderitu Kingori, 2016. "Market Structure, Macroeconomic Shocks, and Banking Risk in Kenya," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 1(2), pages 81-113, December.
    105. Benjamin Lev, 2005. "Book Reviews," Interfaces, INFORMS, vol. 35(3), pages 260-266, June.
    106. Burke, Andrew & van Stel, André, 2014. "Entry and exit in disequilibrium," Journal of Business Venturing, Elsevier, vol. 29(1), pages 174-192.
    107. Parola, Francesco & Veenstra, Albert W., 2008. "The spatial coverage of shipping lines and container terminal operators," Journal of Transport Geography, Elsevier, vol. 16(4), pages 292-299.
    108. Paul de Boer & Bjarne S. Jensen, 2005. "The Expenditure System of CDES Indirect Utility Functions," DEGIT Conference Papers c010_036, DEGIT, Dynamics, Economic Growth, and International Trade.
    109. Mihaela Simionescu (Bratu), 2014. "The Bayesian Modelling Of Inflation Rate In Romania," Romanian Statistical Review, Romanian Statistical Review, vol. 62(2), pages 147-160, June.
    110. Botzen, W.J.W. & Bouwer, L.M. & van den Bergh, J.C.J.M., 2010. "Climate change and hailstorm damage: Empirical evidence and implications for agriculture and insurance," Resource and Energy Economics, Elsevier, vol. 32(3), pages 341-362, August.
    111. Noussair, Charles N. & Offerman, Theo & Suetens, Sigrid & Van de Ven, Jeroen & Van Leeuwen, Boris & Van Veelen, Matthijs, 2014. "Predictably angry: Facial cues provide a credible signal of destructive behavior," IAST Working Papers 14-15, Institute for Advanced Study in Toulouse (IAST).
    112. Lucas Boareto da Aparecida & Sergio Giovanetti Lazzarini & Adriana Bruscato Bortoluzzo, 2022. "Long-term Financing: Exploring the Recent Advances in the Brazilian Bond Market," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(2), pages 210076-2100.
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    115. Wiboonpongse, Aree & Sriboonchitta, Songsak & Chaovanapoonphol, Yaovarate, 2006. "The Demand for Loans for Major Rice in the Upper North of Thailand," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25303, International Association of Agricultural Economists.
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  6. Franses,Philip Hans, 2002. "A Concise Introduction to Econometrics," Cambridge Books, Cambridge University Press, number 9780521520904, January.

    Cited by:

    1. Simplice A. Asongu & Ndemaze Asongu, 2017. "Comparative Determinants of Quality of Growth in Developing Countries," Research Africa Network Working Papers 17/013, Research Africa Network (RAN).
    2. Asongu, Simplice & Nwachukwu, Jacinta, 2017. "Quality of Growth Empirics: Comparative Gaps, Benchmarking and Policy Syndromes," MPRA Paper 83072, University Library of Munich, Germany.
    3. Asongu, Simplice, 2015. "Welfare Spending and Quality of Growth in Developing Countries: Evidence from Hopefuls, Contenders and Best Performers," MPRA Paper 68312, University Library of Munich, Germany.
    4. Gavenas, Ekaterina & Rosendahl, Knut Einar & Skjerpen, Terje, 2015. "CO2-emissions from Norwegian oil and gas extraction," Working Paper Series 07-2015, Norwegian University of Life Sciences, School of Economics and Business.
    5. Philip Hans Franses, 2006. "On modeling panels of time series," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(4), pages 438-456, November.
    6. Mauro Costantini & Claudio Lupi, 2005. "Stochastic convergence among European economies," Economics Bulletin, AccessEcon, vol. 3(38), pages 1-17.

  7. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, January.

    Cited by:

    1. Luciana Juvenal & Mark P. Taylor, 2008. "Threshold adjustment in deviations from the law of one price," Working Papers 2008-027, Federal Reserve Bank of St. Louis.
    2. Bekiros, Stelios & Marcellino, Massimiliano, 2013. "The multiscale causal dynamics of foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 282-305.
    3. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    4. Param Silvapulle & Titi Kanti Lestari & Jae Kim, 2004. "Nonlinear Modelling of Purchasing Power Parity in Indonesia," Econometric Society 2004 Australasian Meetings 316, Econometric Society.
    5. Rodriguez, Gabriel & Sloboda, Michael J., 2005. "Modeling nonlinearities and asymmetries in quarterly revenues of the US telecommunications industry," Structural Change and Economic Dynamics, Elsevier, vol. 16(1), pages 137-158, March.
    6. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, University Library of Munich, Germany, revised 05 Aug 2005.
    7. Giorgio Valente & Mr. Gene L. Leon & Lucio Sarno, 2006. "Nonlinearity in Deviations From Uncovered Interest Parity: An Explanation of the Forward Bias Puzzle," IMF Working Papers 2006/136, International Monetary Fund.
    8. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
    9. Lim, G.C. & McNelis, Paul D., 2008. "Computational Macroeconomics for the Open Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262123061, December.
    10. Alberto Humala, 2005. "Interest rate pass-through and financial crises: do switching regimes matter? the case of Argentina," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 77-94.
    11. Alberto Humala & Gabriel Rodriguez, 2011. "Some Stylized Facts of Returns in the Foreign Exchange and Stock Markets in Peru," Documentos de Trabajo / Working Papers 2011-325, Departamento de Economía - Pontificia Universidad Católica del Perú.
    12. Escribano Alvaro & Torrado María, 2018. "Nonlinear and asymmetric pricing behaviour in the Spanish gasoline market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-19, December.
    13. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    14. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    15. Chukiat Chaiboonsri & Prasert Chaitip, 2012. "A Comparative Analysis of ASEAN Currencies Using a Copula Approach and a Dynamic Copula Approach," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 12(4), pages 39-52.
    16. Martínez Ibáñez, Oscar & Olmo, José, 2008. "A nonlinear threshold model for the dependence of extremes of stationary sequences," Working Papers 2072/5361, Universitat Rovira i Virgili, Department of Economics.
    17. Stein, Michael & Islami, Mevlud & Lindemann, Jens, 2012. "Identifying time variability in stock and interest rate dependence," Discussion Papers 24/2012, Deutsche Bundesbank.
    18. Viviana Fernández, 2002. "How Sensitive is Volatility to Exchange Rate Regimes?," Documentos de Trabajo 135, Centro de Economía Aplicada, Universidad de Chile.
    19. Omay, Nazli C. & Karadagli, Ece C., 2010. "Testing Weak Form Market Efficiency for Emerging Economies: A Nonlinear Approach," MPRA Paper 27312, University Library of Munich, Germany.
    20. Ming Chien Lo & James Morley, 2013. "Bayesian Analysis of Nonlinear Exchange Rate Dynamics and the Purchasing Power Parity Persistence Puzzle," Discussion Papers 2013-05, School of Economics, The University of New South Wales.
    21. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area," Post-Print halshs-00423890, HAL.
    22. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    23. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
    24. Jaehee Kim & Sooyoung Cheon, 2010. "A Bayesian regime‐switching time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 365-378, September.
    25. Benz, Eva & Trück, Stefan, 2009. "Modeling the price dynamics of CO2 emission allowances," Energy Economics, Elsevier, vol. 31(1), pages 4-15, January.
    26. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    27. Marwan Izzeldin & Ana-Maria Fuertes & Anthony Murphy, 2005. "A guided tour of TSMod 4.03," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 691-698.
    28. Mário Jorge Mendonça & Manoel Carlos de Castro Pires & Luiz Alberto Medrano, 2008. "Administração e Sustentabilidade da Dívida Pública no Brasil: Uma Análise para o Período 1995-2007," Discussion Papers 1342, Instituto de Pesquisa Econômica Aplicada - IPEA.
    29. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    30. Bulla, Jan & Bulla, Ingo, 2006. "Stylized facts of financial time series and hidden semi-Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2192-2209, December.
    31. Barry A. Goss & S. Gulay Avsar, 2013. "Simultaneity, Forecasting and Profits in London Copper Futures," Australian Economic Papers, Wiley Blackwell, vol. 52(2), pages 79-96, June.
    32. Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," JRFM, MDPI, vol. 8(3), pages 1-26, August.
    33. Daniel Ventosa-Santaulària & Alfonso Mendoza Velázquez & Manuel Gómez-Zaldívar, 2008. "Varianza condicional de medias móviles no-lineales," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 29-48, November.
    34. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    35. Costas Milas & Jesus Otero & Theodore Panagiotidis, 2001. "Forecasting the spot prices of various coffee types using linear and non-linear error correction models," Borradores de Investigación 2737, Universidad del Rosario.
    36. Orlando Gomes, 2004. "A Continuous-Time Asset Pricing Model with Boundedly Rational Heterogeneous Agents," Finance 0409055, University Library of Munich, Germany.
    37. De Luca, Giovanni & Zuccolotto, Paola, 2006. "Regime-switching Pareto distributions for ACD models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2179-2191, December.
    38. Samira Haddou, 2010. "Non-linéarité de la fonction de réaction des autorités monétaires tunisiennes," Économie et Prévision, Programme National Persée, vol. 195(4), pages 99-110.
    39. Gil-Alana, L.A., 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, Elsevier, vol. 15(1), pages 28-48.
    40. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    41. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
    42. Hui Feng, 2005. "Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?," Econometrics Working Papers 0515, Department of Economics, University of Victoria.
    43. Yavuz, Nilgün Çil & Yilanci, Veli, 2012. "Testing For Nonlinearity In G7 Macroeconomic Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 69-79, September.
    44. Silvia S.W. Lui, 2006. "An Empirical Study of Asian Stock Volatility Using Stochastic Volatility Factor Model: Factor Analysis and Forecasting," Working Papers 581, Queen Mary University of London, School of Economics and Finance.
    45. Hui Feng, 2009. "Real-time or current vintage: does the type of data matter for forecasting and model selection?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 183-193.
    46. Philip Arestis & Andrea Cipollini & Bassam Fattouh, 2002. "Threshold Effects in the U.S. Budget Deficit," Economics Working Paper Archive wp_358, Levy Economics Institute.
    47. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    48. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    49. Philipp Ratz, 2022. "Nonparametric Value-at-Risk via Sieve Estimation," Papers 2205.07101, arXiv.org.
    50. José Luis Torres, 2006. "Modelos Para La Inflación Básica de Bienes Transables y No Transables en Colombia," Borradores de Economia 365, Banco de la Republica de Colombia.
    51. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
    52. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    53. Jedrzej Bialkowski & Serge Darolles & Gaëlle Le Fol, 2012. "Reducing the risk of VWAP orders execution - A new approach to modeling intra-day volume," Post-Print hal-01632822, HAL.
    54. Javier Cabello Sánchez & Juan Antonio Fernández Torvisco & Mariano R. Arias, 2021. "TAC Method for Fitting Exponential Autoregressive Models and Others: Applications in Economy and Finance," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    55. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    56. Dimitrios D. Thomakos & Prasad S. Bhattacharya, 2004. "Forecasting Industry-Level CPI and PPI Inflation: Does Exchange Rate Pass-Through Matter?," Econometric Society 2004 Australasian Meetings 293, Econometric Society.
    57. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
    58. Ryan Lemand, 2003. "The Contagion Effect Between the Volatilities of the NASDAQ-100 and the IT.CA :A Univariate and A Bivariate Switching Approach," Econometrics 0307002, University Library of Munich, Germany, revised 07 Dec 2020.
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