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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. 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).
    2. 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.
    3. 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.
    4. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.
    5. 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.
    6. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    7. 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.
    8. 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).
    9. 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.
    10. 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).
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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).
    23. 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.
    24. 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).
    25. 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).
    26. 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.
    27. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    28. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    29. 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).
    30. 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).
    31. 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).
    32. 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.
    33. 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).
    34. 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.
    35. 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.
    36. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    37. 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).
    38. 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.
    39. 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).
    40. 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).
    41. 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).
    42. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    43. 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.
    44. 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.
    45. 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.
    46. Michael Pedersen, 2024. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," Papers 2404.04105, arXiv.org.
    47. 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.
    48. 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.
    49. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org.
    50. 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.
    51. 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).
    52. 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.
    53. 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.
    54. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    55. 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.
    56. 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.

  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. 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.
    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.

  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. 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.

  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. 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).
    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.
    3. 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.
    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. Philip Hans Franses & Bert Bruijn, 2017. "Benchmarking Judgmentally Adjusted Forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 3-11, January.
    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. 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).
    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.
    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. 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).
    2. Connor Oxenhorn, 2022. "A Multivariate Hawkes Process Model for Stablecoin-Cryptocurrency Depegging Event Dynamics," Papers 2205.06338, arXiv.org.
    3. Pushpa Dissanayake & Teresa Flock & Johanna Meier & Philipp Sibbertsen, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Mathematics, MDPI, vol. 9(21), pages 1-33, November.
    4. Lleo, Sebastien & Ziemba, William, 2018. "A tale of two indexes: predicting equity market downturns in China," LSE Research Online Documents on Economics 118923, London School of Economics and Political Science, LSE Library.
    5. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2015. "Specification Testing in Hawkes Models," Tinbergen Institute Discussion Papers 15-086/III, Tinbergen Institute.
    6. Wei-Zhen Li & Jin-Rui Zhai & Zhi-Qiang Jiang & Gang-Jin Wang & Wei-Xing Zhou, 2020. "Predicting tail events in a RIA-EVT-Copula framework," Papers 2004.03190, arXiv.org, revised Apr 2020.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. Maciej Jagielski & Ryszard Kutner & Didier Sornette, 2016. "Theory of earthquakes interevent times applied to financial markets," Papers 1610.08921, arXiv.org, revised Oct 2016.

  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, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    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. Joseph J. French & Rodrigo Taborda, 2017. "Disentangling the relationship between liquidity and returns in Latin America," Documentos CEDE 15606, Universidad de los Andes, Facultad de Economía, CEDE.

  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, 2017. "Use of unit root methods in early warning of financial crises," ESRB Working Paper Series 45, European Systemic Risk Board.
    2. 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.

  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. 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.
    2. 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.
    3. 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.
    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. 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.
    7. 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.
    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 & 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.
    2. 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.

  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. 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).
    3. 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.
    4. 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).
    5. 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.

  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. Tyran, Jean-Robert & Thomas, Thomas, 2016. "Money Illusion and Household Finance," CEPR Discussion Papers 11643, C.E.P.R. Discussion Papers.
    3. Murota, Ryu-ichiro, 2019. "Negative interest rate policy in a permanent liquidity trap," MPRA Paper 93498, University Library of Munich, Germany.

  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. 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.
    2. 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.
    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. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
    5. 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.

  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, 2014. "Do Experts’ SKU Forecasts Improve after Feedback?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 69-79, January.

  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. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    2. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    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. 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. 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. 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).
    2. Kimberley Scharf & Sarah Smith & Mark Ottoni-Wilhelm, 2022. "Lift and Shift: The Effect of Fundraising Interventions in Charity Space and Time," American Economic Journal: Economic Policy, American Economic Association, vol. 14(3), pages 296-321, August.
    3. 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.
    4. Carlo Gallier & Timo Goeschl & Martin Kesternich & Johannes Lohse & Christiane Reif & Daniel Roemer, 2019. "Inter-charity competition under spatial differentiation: Sorting, crowding, and splillovers," Discussion Papers 19-08, Department of Economics, University of Birmingham.
    5. Damgaard, Mette Trier, 2021. "A decade of nudging: What have we learned?," Nationaløkonomisk tidsskrift, Nationaløkonomisk Forening, vol. 2021(1), pages 1-21.
    6. 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.
    7. 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.
    8. 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.
    9. Maja Adena & Anselm Hager, 2024. "Does Online Fundraising Increase Charitable Giving? A Nationwide Field Experiment on Facebook," CESifo Working Paper Series 10954, CESifo.
    10. 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.
    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.

  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 & Les Oxley & Felix Chan, 2013. "Modelling and Simulation: An Overview," Documentos de Trabajo del ICAE 2013-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

  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 & Les Oxley, 2013. "Coercive Journal Self Citations, Impact Factor, Journal Influence and Article Influence," KIER Working Papers 852, Kyoto University, Institute of Economic Research.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Chang, C-L. & McAleer, M.J., 2014. "Quality Weighted Citations Versus Total Citations in the Sciences and Social Sciences," Econometric Institute Research Papers 50641, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Michael McAleer & Chia-Lin Chang, 2012. "What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance," KIER Working Papers 806, Kyoto University, Institute of Economic Research.
    9. Chang, C-L. & McAleer, M.J., 2013. "Ranking Leading Econometrics Journals Using Citations Data from ISI and RePEc," Econometric Institute Research Papers EI 2013-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Joe Hirschberg & Jenny Lye, 2018. "Grading Journals in Economics: The ABCs of the ABDC," Department of Economics - Working Papers Series 2041, The University of Melbourne.
    11. 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.
    12. 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.
    13. 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.
    14. Chia-Lin Chang & Michael McAleer, 2011. "How Should Journal Quality be Ranked? An Application to Agricultural, Energy, Environmental and Resource Economics," Working Papers in Economics 11/43, University of Canterbury, Department of Economics and Finance.
    15. 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).
    16. Chang, C-L. & McAleer, M.J., 2014. "Ranking Economics and Econometrics ISI Journals by Quality Weighted Citations," Econometric Institute Research Papers EI 2014-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Chia-Lin Chang & Michael McAleer, 2015. "Bibliometric Rankings of Journals Based on the Thomson Reuters Citations Database," Journal of Reviews on Global Economics, Lifescience Global, vol. 4, pages 120-125.
    18. 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.
    19. Chang, C-L. & McAleer, M.J., 2012. "Ranking Journal Quality by Harmonic Mean of Ranks: An Application to ISI Statistics & Probability," Econometric Institute Research Papers EI 2012-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. 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.
    21. 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.
    22. 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.

  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. 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. 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.
    3. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Evaluating Combined Non-Replicable Forecasts," Working Papers in Economics 10/74, University of Canterbury, Department of Economics and Finance.
    4. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," CIRJE F-Series CIRJE-F-729, CIRJE, Faculty of Economics, University of Tokyo.
    5. 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.
    6. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2011. "Evaluating Individual and Mean Non-Replicable Forecasts," KIER Working Papers 773, Kyoto University, Institute of Economic Research.
    7. Jeffrey Frankel, 2011. "A Solution to Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," CID Working Papers 216, Center for International Development at Harvard University.
    8. 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.
    9. 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.
    10. 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.
    11. Alexander HARIN, 2014. "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, vol. 2(2), pages 69-79.
    12. 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.
    13. 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.
    14. 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.
    15. Frankel, Jeffrey A., 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Scholarly Articles 4723209, Harvard Kennedy School of Government.
    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. Badarinza, Cristian & Gross, Marco, 2011. "Macroeconomic vulnerability and disagreement in expectations," Working Paper Series 1407, European Central Bank.
    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. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    4. 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.
    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. Nautz, Dieter & Pagenhardt, Laura & Strohsal, Till, 2017. "The (de-)anchoring of inflation expectations: New evidence from the euro area," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 103-115.
    7. 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.
    8. 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).
    9. 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.

  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. Guidolin, Mariangela & Guseo, Renato, 2014. "Modelling seasonality in innovation diffusion," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 33-40.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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).

  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. 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.
    4. Kunst, Robert M., 2014. "A Combined Nonparametric Test for Seasonal Unit Roots," Economics Series 303, Institute for Advanced Studies.

  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. 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.
    2. Karim Barkat & Raschid Sbia & Youcef Maouchi, 2019. "Empirical evidence on the long and short run determinants of health expenditure in the Arab world," Post-Print hal-01982309, HAL.
    3. 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.
    4. 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.

  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. Jeffrey Frankel, 2011. "A Solution to Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," CID Working Papers 216, Center for International Development at Harvard University.
    2. Frankel, Jeffrey A., 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Scholarly Articles 4723209, Harvard Kennedy School of Government.

  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. 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.
    2. 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.
    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. 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.
    5. 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.
    6. 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.
    7. Hristos Karahalios, 2021. "Contribution of PSC Authorities to Ship Accident Prevention," SN Operations Research Forum, Springer, vol. 2(1), pages 1-18, March.
    8. 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.

  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. 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.
    3. 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.
    4. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Evaluating Combined Non-Replicable Forecasts," Working Papers in Economics 10/74, University of Canterbury, Department of Economics and Finance.
    5. 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.
    6. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," CIRJE F-Series CIRJE-F-729, CIRJE, Faculty of Economics, University of Tokyo.
    7. Michael McAleer & Chia-Lin Chang, 2012. "What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance," KIER Working Papers 806, Kyoto University, Institute of Economic Research.
    8. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2011. "Evaluating Individual and Mean Non-Replicable Forecasts," KIER Working Papers 773, Kyoto University, Institute of Economic Research.
    9. 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.
    10. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    11. 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.
    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. Egor Griva & Irina Butorina & Anatoly Sidorov & Pavel Senchenko, 2022. "Analysis and Forecasting of Sales Funnels," Mathematics, MDPI, vol. 11(1), pages 1-22, December.
    14. 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.
    15. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
    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. Dellaert, Benedict G.C. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "Shopping context and consumers’ mental representation of complex shopping trip decision problems," Journal of Retailing, Elsevier, vol. 84(2), pages 219-232.
    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. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    5. 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.
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Carlo Gallier & Timo Goeschl & Martin Kesternich & Johannes Lohse & Christiane Reif & Daniel Roemer, 2019. "Inter-charity competition under spatial differentiation: Sorting, crowding, and splillovers," Discussion Papers 19-08, Department of Economics, University of Birmingham.
    7. 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).
    8. 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.
    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. Gani Aldashev & Marco Marini & Thierry Verdier, 2013. "Brothers in alms? coordination between nonprofits on markets for donations," Carlo Alberto Notebooks 293, Collegio Carlo Alberto.
    12. 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).
    13. Eckel, Catherine & Guney, Begum & Uler, Neslihan, 2020. "Independent vs. Coordinated Fundraising: Understanding the Role of Information," European Economic Review, Elsevier, vol. 127(C).
    14. Leeflang, Peter, 2011. "Paving the way for “distinguished marketing”," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 76-88.
    15. 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.
    16. Ilya O. Ryzhov & Bin Han & Jelena Bradić, 2016. "Cultivating Disaster Donors Using Data Analytics," Management Science, INFORMS, vol. 62(3), pages 849-866, March.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    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, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    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. Frank A.G. den Butter & Pieter W. Jansen, 2008. "Beating the Random Walk: a Performance Assessment of Long-term Interest Rate Forecasts," Tinbergen Institute Discussion Papers 08-102/3, Tinbergen Institute.
    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. 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.
    3. 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.
    4. 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.

  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. & Galvão, Ana Beatriz, 2009. "First Announcements and Real Economic Activity," The Warwick Economics Research Paper Series (TWERPS) 885, University of Warwick, Department of Economics.

  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. S Holly & M Hashem Pesaran & T Yamagata, "undated". "Spatial and Temporal Diffusion of House Prices in the UK," Discussion Papers 09/32, Department of Economics, University of York.
    2. 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.
    3. Dominik Blatt & Kausik Chaudhuri & Hans Manner, 2021. "Spillover in the UK Housing Market," Graz Economics Papers 2021-13, University of Graz, Department of Economics.
    4. James D. Hamilton & Michael T. Owyang, 2011. "The Propagation of Regional Recessions," NBER Working Papers 16657, National Bureau of Economic Research, Inc.
    5. Katharina Pijnenburg, 2013. "The Spatial Dimension of US House Price Developments," Discussion Papers of DIW Berlin 1270, DIW Berlin, German Institute for Economic Research.
    6. 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.
    7. 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.
    8. 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".
    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, 2014. "The Spatial Dimension of US House Price Developments," ERSA conference papers ersa14p127, European Regional Science Association.
    11. 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.
    12. Sergei S. Shibaev, 2016. "Recession Propagation In Small Regional Economies: Spatial Spillovers And Endogenous Clustering," Working Paper 1369, Economics Department, Queen's University.
    13. Bing Zhu & Dorinth van Dijk & Colin Lizieri, 2021. "Price diffusion across international private commercial real estate markets," Working Papers 732, DNB.
    14. 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.

  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, 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.
    2. 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.

  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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Claussen, Jörg & Falck, Oliver & Grohsjean, Thorsten, 2012. "The strength of direct ties: Evidence from the electronic game industry," International Journal of Industrial Organization, Elsevier, vol. 30(2), pages 223-230.
    8. 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.
    9. 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.
    10. 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.
    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. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Alexei Parakhonyak & Nick Vikander, 2013. "Optimal Sales Schemes for Network Goods," Discussion Papers 13-11, University of Copenhagen. Department of Economics.
    19. 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.
    20. 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.
    21. 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.
    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. 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.
    24. 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.
    25. 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.
    26. Joost Rietveld & J. P. Eggers, 2018. "Demand Heterogeneity in Platform Markets: Implications for Complementors," Organization Science, INFORMS, vol. 29(2), pages 304-322, April.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    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. Yanjie Wu & Sujuan Wang, 2021. "Sustainable Market Entry Strategy under a Supply Chain Environment," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. Van Hove, Leo, 2016. "Testing Metcalfe's law: Pitfalls and possibilities," Information Economics and Policy, Elsevier, vol. 37(C), pages 67-76.
    46. Narayanan, V.K. & Chen, Tianxu, 2012. "Research on technology standards: Accomplishment and challenges," Research Policy, Elsevier, vol. 41(8), pages 1375-1406.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. 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.
    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. 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.
    2. Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    3. 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.

  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. 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.
    2. Drago, Carlo & Millo, Francesco & Ricciuti, Roberto & Santella, Paolo, 2015. "Corporate governance reforms, interlocking directorship and company performance in Italy," International Review of Law and Economics, Elsevier, vol. 41(C), pages 38-49.
    3. 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.
    4. 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.
    5. 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.
    6. Gloria ESTAPE-DUBREUIL & Consol TORREGUITART-MIRADA, 2015. "Governance Mechanisms, Social Performance Disclosure and Performance in Microfinance: Does Legal Status Matter?," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 86(1), pages 137-155, March.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Battistin, Erich & Graziano, Clara & Parigi, Bruno M., 2012. "Connections and performance in bankers’ turnover," European Economic Review, Elsevier, vol. 56(3), pages 470-487.

  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. 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.
    2. Meer, Jonathan & Rosen, Harvey S., 2011. "The ABCs of charitable solicitation," Journal of Public Economics, Elsevier, vol. 95(5), pages 363-371.
    3. Jonathan Meer & Harvey S. Rosen, 2008. "The ABCs of Charitable Solicitation," Working Papers 1057, Princeton University, Department of Economics, Center for Economic Policy Studies..
    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. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    7. 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 Papers 416, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. 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.
    9. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    10. Francesco Ravazzolo & Marco J. Lombardi, 2012. "Oil price density forecasts: Exploring the linkages with stock markets," Working Papers No 3/2012, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    11. 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.
    12. 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.
    13. 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.

  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. 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).
    2. 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.
    3. 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.
    4. Hense, Jonas & Hübner, Alexander, 2022. "Assortment optimization in omni-channel retailing," European Journal of Operational Research, Elsevier, vol. 301(1), pages 124-140.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    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. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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).
    17. Gecili, Hakan & Parikh, Pratik J., 2022. "Joint shelf design and shelf space allocation problem for retailers," Omega, Elsevier, vol. 111(C).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Schäfer, Fabian & Hense, Jonas & Hübner, Alexander, 2023. "An analytical assessment of demand effects in omni-channel assortment planning," Omega, Elsevier, vol. 115(C).
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    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," Post-Print halshs-00754487, HAL.
    2. 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.
    3. 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.
    4. 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.
    5. Meer, Jonathan & Rosen, Harvey S., 2011. "The ABCs of charitable solicitation," Journal of Public Economics, Elsevier, vol. 95(5), pages 363-371.
    6. Jonathan Meer & Harvey S. Rosen, 2008. "The ABCs of Charitable Solicitation," Working Papers 1057, Princeton University, Department of Economics, Center for Economic Policy Studies..

  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. Long Gao & Birendra K. Mishra, 2019. "The Role of Market Evolution in Channel Contracting," Management Science, INFORMS, vol. 67(5), pages 2432-2441, May.
    2. 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.
    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. 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.
    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. 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.
    4. 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.
    5. 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.
    6. 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).

  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. Stephan Seiler, 2010. "The impact of search costs on consumer behavior: a dynamic approach," 2010 Meeting Papers 559, Society for Economic Dynamics.
    3. 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.
    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, 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.

  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. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
    2. 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.
    3. Guidolin, Mariangela & Guseo, Renato, 2014. "Modelling seasonality in innovation diffusion," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 33-40.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

  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. 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.
    2. 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.
    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. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. Giovanni Modanese, 2023. "The Network Bass Model with Behavioral Compartments," Stats, MDPI, vol. 6(2), pages 1-13, March.
    11. 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).
    12. 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.
    13. Jinyoung Kim & Kanghyock Koh, 2014. "Incentives for Journal Editors," Canadian Journal of Economics, Canadian Economics Association, vol. 47(1), pages 348-371, February.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Gelper, Sarah & Stremersch, Stefan, 2014. "Variable selection in international diffusion models," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 356-367.
    20. 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.
    21. 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.

  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, 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.
    2. 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.
    3. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    4. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    5. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    6. 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. Philip Hans Franses, 2011. "Model selection for forecast combination," Applied Economics, Taylor & Francis Journals, vol. 43(14), pages 1721-1727.
    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. 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.
    4. 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.
    5. 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.
    6. 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.

  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. 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.
    5. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2008. "Modeling the Effectiveness of Hourly Direct-Response Radio Commercials," ERIM Report Series Research in Management ERS-2008-019-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.
    6. 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.
    7. 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.
    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 J. Burger & Martijn Hendriks & Emma Pleeging & Jan C. Ours, 2020. "The joy of lottery play: evidence from a field experiment," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1235-1256, December.

  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. 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.
    2. 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.
    3. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    4. 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.
    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. 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.
    7. Nina Vujanovic & Bruno Casella & Richard Bolwijn, . "Forecasting global FDI: a panel data approach," UNCTAD Transnational Corporations Journal, United Nations Conference on Trade and Development.
    8. Allenby, Greg M., 2017. "Structural forecasts for marketing data," International Journal of Forecasting, Elsevier, vol. 33(2), pages 433-441.
    9. 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.
    10. 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.
    11. 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).

  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. 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. 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.
    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. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2008. "Modeling the Effectiveness of Hourly Direct-Response Radio Commercials," ERIM Report Series Research in Management ERS-2008-019-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.
    5. 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.
    6. 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.
    7. 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.
    8. Dawes, John G., 2012. "Brand-Pack Size Cannibalization Arising from Temporary Price Promotions," Journal of Retailing, Elsevier, vol. 88(3), pages 343-355.

  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. 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.
    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. Alexander Faehnle & Mariangela Guidolin, 2021. "Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes," Forecasting, MDPI, vol. 3(1), pages 1-15, March.
    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. 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. 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.
    2. 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.
    3. 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.
    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. 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.
    6. 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.
    7. 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.

  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. 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.
    2. 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.
    3. Oleg Korenok & Bruce Mizrach, 2004. "The Microeconomics of Macroeconomic Asymmetries: Sectoral Driving Forces and Firm Level Characteristics," Computing in Economics and Finance 2004 266, Society for Computational Economics.

  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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Zhuoxin Li & Jason A. Duan, 2014. "Dynamic Strategies for Successful Online Crowdfunding," Working Papers 14-09, NET Institute.
    9. Andros Kourtellos & Charalambos G. Tsangarides, 2022. "Robust Correlates of Growth Spells: Do Inequality and Redistribution Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1302-1328, December.
    10. 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).
    11. Bijwaard, Govert, 2011. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," IZA Discussion Papers 5748, Institute of Labor Economics (IZA).
    12. 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.
    13. 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.
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

  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. 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.
    2. Richards, Timothy J. & Gómez, Miguel I. & Printezis, Iryna, 2014. "Hysteresis, Price Acceptance, and Reference Prices," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 164872, Agricultural and Applied Economics Association.

  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. Francisco Salas-Molina & Francisco J. Martin & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Josep Ll. Arcos, 2016. "Empowering cash managers to achieve cost savings by improving predictive accuracy," Papers 1605.04219, arXiv.org.
    2. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    3. 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.
    4. 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.
    5. 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).
    6. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    7. 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.
    8. 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.
    9. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    10. 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.
    11. 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.
    12. 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.
    13. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    14. Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
    15. Nikolay Robinzonov & Klaus Wohlrabe, 2008. "Freedom of Choice in Macroeconomic Forecasting: An Illustration with German Industrial Production and Linear Models," ifo Working Paper Series 57, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    16. 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.
    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. 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.
    19. 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.
    20. 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.
    21. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    29. 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.
    30. 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.
    31. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    32. 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.
    33. Zuzanna Karolak, 2021. "Energy prices forecasting using nonlinear univariate models," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 577-598.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. Patrick T. kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2014. "Forecasting South African Inflation Using Non-Linear Models: A Weighted Loss-Based Evaluation," Working Papers 201416, University of Pretoria, Department of Economics.
    39. 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.
    40. Kauppi, Heikki & Virtanen, Timo, 2021. "Boosting nonlinear predictability of macroeconomic time series," International Journal of Forecasting, Elsevier, vol. 37(1), pages 151-170.
    41. 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.
    42. 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.
    43. 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.
    44. Michal Franta, 2013. "The Effect of Non-Linearity Between Credit Conditions and Economic Activity on Density Forecasts," Working Papers 2013/09, Czech National Bank.
    45. Heikki Kauppi & Timo Virtanen, 2018. "Boosting Non-linear Predictabilityof Macroeconomic Time Series," Discussion Papers 124, Aboa Centre for Economics.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    51. 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).
    52. 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.
    53. 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.
    54. 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.
    55. He, Kaijian & Yu, Lean & Tang, Ling, 2015. "Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology," Energy, Elsevier, vol. 91(C), pages 601-609.
    56. 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.
    57. Dat Thanh Tran & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2021. "Bilinear Input Normalization for Neural Networks in Financial Forecasting," Papers 2109.00983, arXiv.org.
    58. 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.
    59. 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.

  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. 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.
    2. 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.
    3. Chenavaz, Régis & Drouard, Joeffrey & Escobar, Octavio R. & Karoubi, Bruno, 2018. "Convenience pricing in online retailing: Evidence from Amazon.com," Economic Modelling, Elsevier, vol. 70(C), pages 127-139.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Yassine Bouhdaoui & David Bounie & Abel François, 2014. "Convenient Prices, Cash Payments and Price Rigidity," Post-Print hal-02286878, HAL.
    12. Carlos A. Arango A., 2004. "La Demanda De Especies Monetarias En Colombia: Estructura Y Pronóstico," Borradores de Economia 2964, Banco de la Republica.
    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.

  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. 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.
    2. 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.
    3. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Li, Leon, 2017. "Dynamic correlations and domestic-global diversification," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 280-290.
    5. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    6. Christian Hafner & Helmut Herwartz, 2008. "Analytical quasi maximum likelihood inference in multivariate volatility models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(2), pages 219-239, March.
    7. 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.
    8. 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.
    9. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    10. 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.
    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. 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.
    14. Amine Lahiani & Khaled Guesmi, 2014. "Commodity Price Correlation and Time varying Hedge Ratios," Working Papers 2014-142, Department of Research, Ipag Business School.
    15. 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.
    16. Billio, Monica & Caporin, Massimiliano, 2009. "A generalized Dynamic Conditional Correlation model for portfolio risk evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2566-2578.
    17. 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).
    18. Vargas, Gregorio A., 2008. "What Drives the Dynamic Conditional Correlation of Foreign Exchange and Equity Returns?," MPRA Paper 7174, University Library of Munich, Germany.
    19. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. 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.
    21. 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.

  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. 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.
    2. Grinis, Inna, 2017. "Trend growth durations & shifts," LSE Research Online Documents on Economics 85126, London School of Economics and Political Science, LSE Library.
    3. 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.

  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. 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.
    2. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    3. Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
    4. 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.
    5. Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 03/2015, Stellenbosch University, Department of Economics.
    6. 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.
    7. 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.
    8. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative tests for correct specification of conditional predictive densities," Economics Working Papers 1416, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2017.
    10. Costas Milas & Philip Rothman, 2007. "Out-of-Sample Forecasting of Unemployment Rates with Pooled STVECM Forecasts," Working Paper series 49_07, Rimini Centre for Economic Analysis.
    11. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    12. 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.
    13. Goodness C. Aye & Mehmet Balcilar Author-Name-First Mehmet & Rangan Gupta & Anandamayee Majumdar, 2014. "Forecasting Aggregate Retail Sales: The Case of South Africa," Working Papers 15-21, Eastern Mediterranean University, Department of Economics.
    14. 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.
    15. Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2014. "The Role of Economic Policy Uncertainty in Forecasting US Inflation Using a VARFIMA Model," Working Papers 201460, University of Pretoria, Department of Economics.
    16. Engel, J. & Haugh, D. & Pagan, A., 2005. "Some methods for assessing the need for non-linear models in business cycle analysis," International Journal of Forecasting, Elsevier, vol. 21(4), pages 651-662.
    17. 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.
    18. 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.
    19. Mehmet Balcilar & Rangan Gupta & Renee van Eyden & Kirsten Thompson, 2015. "Comparing the Forecasting Ability of Financial Conditions Indices: The Case of South Africa," Working Papers 15-06, Eastern Mediterranean University, Department of Economics.
    20. 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.
    21. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 201230, University of Pretoria, Department of Economics.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.

  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. 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.
    2. Eric Anderson & Nanda Kumar, 2007. "Price competition with repeat, loyal buyers," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 333-359, December.

  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.

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    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. Seung Hyun Hong & Peter C. B. Phillips, 2005. "Testing Linearity in Cointegrating Relations with an Application to Purchasing Power Parity," Cowles Foundation Discussion Papers 1541, Cowles Foundation for Research in Economics, Yale University.
    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. 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.
    2. 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.
    3. 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.
    4. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
    5. Beck, Jonathan, 2008. "Diderot´s rule," Discussion Papers, Research Unit: Competition and Innovation SP II 2008-13, WZB Berlin Social Science Center.
    6. 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).
    7. 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.
    8. Claudia Furlan & Cinzia Mortarino, 2020. "Comparison among simultaneous confidence regions for nonlinear diffusion models," Computational Statistics, Springer, vol. 35(4), pages 1951-1991, December.
    9. 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.
    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. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. H.P. Boswijk & D. Fok & P.-H. Franses, 2006. "A New Multivariate Product Growth Model," Tinbergen Institute Discussion Papers 06-027/4, Tinbergen Institute.
    17. 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.
    18. 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.
    19. 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.
    20. 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).
    21. International Monetary Fund, 2005. "Mauritius: Selected Issues and Statistical Appendix," IMF Staff Country Reports 2005/280, International Monetary Fund.
    22. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    23. 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.
    24. 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.
    25. 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.
    26. 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).
    27. 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.
    28. 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.
    29. 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.
    30. 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.

  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. 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.
    3. Silvia Banfi & Mehdi Farsi & Massimo Filippini & Martin Jakob, 2005. "Willingness to Pay for Energy-Saving Measures in Residential Buildings," CEPE Working paper series 05-41, CEPE Center for Energy Policy and Economics, ETH Zurich.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. Rousseau, Ronald & Hu, Xiaojun, 2013. "Two time series, their meaning and some applications," Journal of Informetrics, Elsevier, vol. 7(3), pages 603-610.

  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. 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.
    3. Franses, Philip Hans & Kippers, Jeanine, 2007. "An empirical analysis of euro cash payments," European Economic Review, Elsevier, vol. 51(8), pages 1985-1997, November.
    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. Lake, James & Millimet, Daniel L., 2016. "An empirical analysis of trade-related redistribution and the political viability of free trade," Journal of International Economics, Elsevier, vol. 99(C), pages 156-178.
    2. Staus, Alexander, 2007. "An Ordinal Regression Model using Dealer Satisfaction Data," Working Papers 98632, Universitaet Hohenheim, Institute of Agricultural Policy and Agricultural Markets.
    3. Jan Schiefer & Monika Hartmann, 2008. "Determinants of competitive advantage for German food processors," Agribusiness, John Wiley & Sons, Ltd., vol. 24(3), pages 306-319.
    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. 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.
    2. 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.
    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, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    2. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    3. Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil).
    4. 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).

  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. 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.
    2. 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.
    3. 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.
    4. Xu, Ke-Li, 2012. "Robustifying multivariate trend tests to nonstationary volatility," Journal of Econometrics, Elsevier, vol. 169(2), pages 147-154.
    5. Pierre Perron & Tomoyoshi Yabu, 2007. "Estimating Deterministic Trend with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2007-020, Boston University - Department of Economics.
    6. 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.
    7. Yonghui Zhang & Liangjun Su & Peter C. B. Phillips, 2012. "Testing for common trends in semi‐parametric panel data models with fixed effects," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 56-100, February.
    8. Nuno Sobreira & Luis C. Nunes, 2016. "Tests for Multiple Breaks in the Trend with Stationary or Integrated Shocks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 394-411, June.
    9. 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.
    10. 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.
    11. R. Velazquez & A.E. Noriega & L.M. Soria, 2004. "International Evidence on Monetary Neutrality Under Broken Trend Stationary Models," Econometric Society 2004 Latin American Meetings 57, Econometric Society.
    12. 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.
    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. 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.

  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. 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.
    2. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    9. 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.
    10. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    11. Luis A. Gil-Alana, 2006. "Fractional integration and structural breaks at unknown periods of time," Faculty Working Papers 16/06, School of Economics and Business Administration, University of Navarra.
    12. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2006. "Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 142(1), pages 67-91, April.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Georgios P. Kouretas & Mark E. Wohar, 2012. "The dynamics of inflation: a study of a large number of countries," Applied Economics, Taylor & Francis Journals, vol. 44(16), pages 2001-2026, June.
    22. 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.
    23. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2018. "Long-Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation," Working Papers 201869, University of Pretoria, Department of Economics.
    24. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    25. 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.
    26. Florian Heinen & Philipp Sibbertsen & Robinson Kruse, 2009. "Forecasting long memory time series under a break in persistence," CREATES Research Papers 2009-53, Department of Economics and Business Economics, Aarhus University.
    27. 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.
    28. Mboya, Mwasi & Sibbertsen, Philipp, 2022. "Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory," Hannover Economic Papers (HEP) dp-705, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    29. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 594-616.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
    38. 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.
    39. 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.
    40. 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.
    41. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    42. 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.
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. Galdi, Giulio & Casarin, Roberto & Ferrari, Davide & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Nowcasting industrial production using linear and non-linear models of electricity demand," Energy Economics, Elsevier, vol. 126(C).
    8. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    9. 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.
    10. 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.
    11. Beckmann, Joscha, 2011. "Nonlinear Adjustment, Purchasing Power Parity and the Role of Nominal Exchange Rates and Prices," Ruhr Economic Papers 272, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    12. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    13. Malgorzata Olszak & Mateusz Pipien & Iwona Kowalska & Sylwia Roszkowska, 2015. "The Impact Of Capital On Lending In Economic Downturns And Investor Protection – The Case Of Large Eu Banks," Faculty of Management Working Paper Series 62015, University of Warsaw, Faculty of Management.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    20. 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.
    21. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    22. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, vol. 27(5), pages 1103-1115, September.
    23. 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.
    24. 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.
    25. 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).
    26. 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.
    27. 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.

  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. Jamel Gatfaoui & Eric Girardin, 2015. "Comovement of Chinese provincial business cycles," Post-Print hal-01456105, HAL.
    2. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    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. 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.
    3. 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.

  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. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
    3. 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.
    4. 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.

  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, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    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.

    Cited by:

    1. 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.
    2. David A. Schweidel & George Knox, 2013. "Incorporating Direct Marketing Activity into Latent Attrition Models," Marketing Science, INFORMS, vol. 32(3), pages 471-487, May.
    3. 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.
    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. 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.
    6. 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.
    7. 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.
    8. Haupt, Johannes & Lessmann, Stefan, 2022. "Targeting customers under response-dependent costs," European Journal of Operational Research, Elsevier, vol. 297(1), pages 369-379.
    9. 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.
    10. 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.
    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. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Johannes Haupt & Stefan Lessmann, 2020. "Targeting customers under response-dependent costs," Papers 2003.06271, arXiv.org, revised Aug 2021.
    17. 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.
    18. 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.

  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. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    2. 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.
    3. 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.
    4. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    12. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2017. "Testing the Fisher Hypothesis in the G-7 Countries Using I(d) Techniques," Discussion Papers of DIW Berlin 1667, DIW Berlin, German Institute for Economic Research.
    13. Mboya, Mwasi & Sibbertsen, Philipp, 2022. "Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory," Hannover Economic Papers (HEP) dp-705, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. 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.
    15. 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.
    16. Goliński, Adam & Zaffaroni, Paolo, 2016. "Long memory affine term structure models," Journal of Econometrics, Elsevier, vol. 191(1), pages 33-56.
    17. 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.
    18. 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.
    19. 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.
    20. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    21. 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.
    22. 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.
    23. 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.

  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.

    Cited by:

    1. 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.
    2. 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.

  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.

    Cited by:

    1. 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.
    2. 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.

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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.

    Cited by:

    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. 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.
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    437. Javed Ahmad Bhat & Md Zulquar Nain & Sajad Ahmad Bhat, 2024. "Exchange rate pass‐through to consumer prices in India – nonlinear evidence from a smooth transition model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 927-942, January.
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    442. Po-Chin Wu & Sheng-Chieh Pan & Xue-Ling Tai, 2015. "Non-linearity, persistence and spillover effects in stock returns: the role of the volatility index," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 597-613, August.
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    447. 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.
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    451. Gabreyohannes, Emmanuel, 2010. "A nonlinear approach to modelling the residential electricity consumption in Ethiopia," Energy Economics, Elsevier, vol. 32(3), pages 515-523, May.
    452. Wu, Po-Chin & Liu, Shiao-Yen & Chen, Che-Ying, 2016. "Re-examining risk premiums in the Fama–French model: The role of investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 154-171.
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    457. Jian Chai & Limin Xing & Quanying Lu & Ting Liang & Kin Keung Lai & Shouyang Wang, 2016. "The Non-Linear Effect of Chinese Financial Developments on Energy Supply Structures," Sustainability, MDPI, vol. 8(10), pages 1-21, October.
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  139. Boswijk, H.P. & van Dijk, D. & Franses, P.H., 2000. "Asymmetric and Common Abssorbtion of Shocks in Nonlinear Autoregressive Models," CeNDEF Working Papers 00-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. 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.
    2. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    3. Galvão, Ana Beatriz C., 2003. "Multivariate Threshold Models: TVARs and TVECMs," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(1), May.
    4. 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.
    5. Ivan Paya & David A. Peel, 2004. "Temporal Aggregation Of An Estar Process: Some Implications For Purchasing Power Parity Adjustment," Working Papers. Serie AD 2004-25, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. 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.
    7. 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.
    8. Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), 2013. "Handbook of Research Methods and Applications in Empirical Finance," Books, Edward Elgar Publishing, number 14545.
    9. 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.
    10. 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.
    11. Gabreyohannes, Emmanuel, 2010. "A nonlinear approach to modelling the residential electricity consumption in Ethiopia," Energy Economics, Elsevier, vol. 32(3), pages 515-523, May.
    12. 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.

  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.

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    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.

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    1. Raimundo Soto, 2000. "Ajuste Estacional e Integración en Variables Macroeconómicas," Working Papers Central Bank of Chile 73, Central Bank of Chile.
    2. Adnen Ben Nasr & Mehmet Balcilar & Ahdi N. Ajmi & Goodness C. Aye & Rangan Gupta & Reneé van Eyden, 2014. "Causality between Inflation and Inflation Uncertainty in South Africa: Evidence from a Markov-Switching Vector Autoregressive Model," Working Papers 201453, University of Pretoria, Department of Economics.
    3. 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.
    4. Nicholas Taylor, 2004. "A New Econometric Model Of Index Arbitrage," Royal Economic Society Annual Conference 2004 69, Royal Economic Society.
    5. 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].
    6. 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.
    7. Kumawat, Lokendra, 2010. "Effect of Rainfall on Seasonals in Indian Manufacturing Production: Evidence from Sectoral Data," MPRA Paper 25300, University Library of Munich, Germany.

  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. P. Geoffrey Allen & Robert Fildes, 2005. "Levels, Differences and ECMs – Principles for Improved Econometric Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 881-904, December.
    3. Jacek Kotlowski, 2005. "Money and prices in the Polish economy. Seasonal cointegration approach," Working Papers 20, Department of Applied Econometrics, Warsaw School of Economics.
    4. 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.
    5. Justyna Wr'oblewska, 2020. "Bayesian analysis of seasonally cointegrated VAR model," Papers 2012.14820, arXiv.org, revised Apr 2021.
    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. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    9. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.

  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.

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    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.

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    1. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2004. "Non-linearities and fractional integration in the US unemployment rate," HWWA Discussion Papers 259, Hamburg Institute of International Economics (HWWA).

  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. 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).
    2. 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.
    3. 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.
    4. 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.
    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. 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.
    7. 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.

  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. 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.

  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. 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.
    3. 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.
    4. 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.
    5. 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).
    6. J. S. Cramer, 2004. "Scoring bank loans that may go wrong: a case study," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(3), pages 365-380, August.
    7. 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).

  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. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    2. Randall E. Parker & Phillip Rothman & Original: August 2000. This version: June 2003., "undated". "An Examination of the Asymmetric Effects of Money Supply Shocks in the Pre-World War I and Interwar Periods," Working Papers 0011, East Carolina University, Department of Economics.
    3. Gabriella Legrenzi & Costas Milas, 2004. "Non-linear real exchange rate effects in the UK labour market," International Finance 0411007, University Library of Munich, Germany.
    4. 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.
    5. 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.
    6. Jawadi Fredj & Koubaa Yousra, 2004. "Threshold Cointegration between Stock Returns : An application of STECM Models," Econometrics 0412001, University Library of Munich, Germany.
    7. 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.
    8. 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.
    9. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Maximo Camacho, 2002. "Nonlinear stochastic trends and economic fluctuations," Computing in Economics and Finance 2002 274, Society for Computational Economics.
    16. Peter Martey Addo, 2014. "Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input," Papers 1407.7738, arXiv.org.
    17. 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.
    18. 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.

  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. 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.
    2. 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.
    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. 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.
    3. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    4. 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.
    5. David EA Giles, 2005. "Output Convergence and International Trade: Time-Series and Fuzzy Clustering Evidence for New Zealand and her Trading Partners, 1950 - 1992," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 14(1), pages 93-114.
    6. 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.
    7. 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.
    8. Irfan Civcir, 2002. "Before The Fall Was The Turkish Lira Overvalued?," Working Papers 0220, Economic Research Forum, revised 11 Jul 2002.
    9. 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.
    10. 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.
    11. 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.
    12. Aurelijus Dabušinskas, 2005. "Money and Prices in Estonia," Bank of Estonia Working Papers 2005-07, Bank of Estonia, revised 10 Nov 2005.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Kenneth G. Stewart & Michael C. Webb, 2003. "Capital Taxation, Globalization, and International Tax Competition," Econometrics Working Papers 0301, Department of Economics, University of Victoria.
    18. 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.
    19. Kaili Shen & David E. Giles, 2005. "Rational Exuberance at the Mall: Addiction to Carrying a Credit Card Balance," Econometrics Working Papers 0508, Department of Economics, University of Victoria.
    20. 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.
    21. 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.
    22. 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.
    23. 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).
    24. 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.
    25. Binner, Jane & Elger, Thomas, 2002. "The UK Personal Sector Demand for Risky Money," Working Papers 2002:9, Lund University, Department of Economics.
    26. 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.
    27. 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.

  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. 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.
    2. Wanbing Zhang & Sisi Zhang & Peibiao Zhao, 2019. "On Double Value at Risk," Risks, MDPI, vol. 7(1), pages 1-22, March.
    3. Patricia Chelley-Steeley & Antonios Siganos, 2005. "Momentum Profits in Alternative Stock Market Structures," Money Macro and Finance (MMF) Research Group Conference 2005 63, Money Macro and Finance Research Group.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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 9780521770415, September.
    11. 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.
    12. 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).
    13. 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.
    14. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    15. 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.
    16. Nicholas Taylor, 2004. "A New Econometric Model Of Index Arbitrage," Royal Economic Society Annual Conference 2004 69, Royal Economic Society.
    17. 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).
    18. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    19. 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.
    20. 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.
    21. 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.
    22. Jürgen Gaul & Erik Theissen, 2015. "A Partially Linear Approach to Modeling the Dynamics of Spot and Futures Prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 371-384, April.
    23. 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.
    24. 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.
    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. 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.

  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. 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. 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).
    2. 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.
    3. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. Ramazan Gencay & Ege Yazgan, 2017. "When Are Wavelets Useful Forecasters?," Working Papers 1704, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    9. Costas Milas & Philip Rothman, 2007. "Out-of-Sample Forecasting of Unemployment Rates with Pooled STVECM Forecasts," Working Paper series 49_07, Rimini Centre for Economic Analysis.
    10. 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.
    11. 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).
    12. 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.
    13. Sánchez, Ismael, 2009. "Graphical identification of TAR models," DES - Working Papers. Statistics and Econometrics. WS ws097723, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Frédérique Bec & Othman Bouabdallah & Laurent Ferrara, 2013. "The European Way out of Recession," Post-Print hal-02980626, HAL.
    15. 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.
    16. 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.
    17. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    18. Bec, Frédérique & Bouabdallah, Othman & Ferrara, Laurent, 2014. "The way out of recessions: A forecasting analysis for some Euro area countries," International Journal of Forecasting, Elsevier, vol. 30(3), pages 539-549.
    19. 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.
    20. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    21. 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.
    22. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    23. 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.
    24. 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.
    25. Manzan, Sebastiano & Zerom, Dawit, 2008. "A bootstrap-based non-parametric forecast density," International Journal of Forecasting, Elsevier, vol. 24(3), pages 535-550.
    26. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    27. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    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. 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.
    30. 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.
    31. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.

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    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.

  159. 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.

    Cited by:

    1. 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.
    2. López Villavicencio, Antonia, 2008. "Nonlinearities or outliers in real exchange rates?," Economic Modelling, Elsevier, vol. 25(4), pages 714-730, July.

  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. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    3. 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.
    4. 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.
    5. 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.
    6. McMillan, David G. & Wohar, Mark E., 2010. "Persistence and time-varying coefficients," Economics Letters, Elsevier, vol. 108(1), pages 85-88, July.
    7. 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.
    8. 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.
    9. 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.
    10. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    11. 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.
    12. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    13. 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.
    14. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    21. Luis Alberiko Gil-Alaña & Olanrewaju L. Shittu & OlaOluwa S. Yaya, 2013. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," NCID Working Papers 12/2013, Navarra Center for International Development, University of Navarra.
    22. 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.
    23. Haldrup; Niels & Morten Oerregaard Nielsen, 2005. "Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices," Economics Working Papers 2005-18, Department of Economics and Business Economics, Aarhus University.
    24. 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.
    25. 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.
    26. 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.
    27. Morana, Claudio, 2000. "Measuring core inflation in the euro area," Working Paper Series 36, European Central Bank.
    28. Dennis Alvaro & Ángel Guillén & Gabriel Rodríguez, 2017. "Modelling the volatility of commodities prices using a stochastic volatility model with random level shifts," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(1), pages 71-103, February.
    29. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. Georgios P. Kouretas & Mark E. Wohar, 2012. "The dynamics of inflation: a study of a large number of countries," Applied Economics, Taylor & Francis Journals, vol. 44(16), pages 2001-2026, June.
    35. 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.
    36. 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.
    37. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
    38. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2018. "Long-Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation," Working Papers 201869, University of Pretoria, Department of Economics.
    39. 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.
    40. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2012. "Are Labor Force Participation Rates Really Non-Stationary? Evidence from Three OECD Countries," ERC Working Papers 1206, ERC - Economic Research Center, Middle East Technical University, revised Aug 2012.
    41. 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.
    42. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    43. 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.
    44. 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].
    45. Bob Nobay & Ivan Paya & David A. Peel, 2007. "Inflation Dynamics in the US -A Nonlinear Perspective," FMG Discussion Papers dp601, Financial Markets Group.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. Haldrup, Niels & Nielsen, Morten Orregaard, 2007. "Estimation of fractional integration in the presence of data noise," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3100-3114, March.
    54. 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.
    55. Bos, Charles S, 2004. "Time Series Modelling using TSMod 3.24," International Journal of Forecasting, Elsevier, vol. 20(3), pages 515-522.
    56. 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.
    57. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    58. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Long-memory dynamics in a SETAR model - applications to stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 391-406, December.
    59. 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.
    60. 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.
    61. 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.
    62. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    63. 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.
    64. 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.
    65. 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.
    66. 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.
    67. Chih-Chiang Hsu, 2000. "Long Memory or Structural Change: Testing Method and Empirical Examination," Econometric Society World Congress 2000 Contributed Papers 0867, Econometric Society.
    68. 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.
    69. 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.
    70. 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.
    71. 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.
    72. 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.
    73. 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.
    74. 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.
    75. 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.

  161. Franses, Ph.H.B.F. & Paap, R., 1998. "Modelling asymmetric persistence over the business cycle," Econometric Institute Research Papers EI 9852, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2004. "Non-linearities and fractional integration in the US unemployment rate," HWWA Discussion Papers 259, Hamburg Institute of International Economics (HWWA).

  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. 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. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
    3. Carnero, María Ángeles, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. 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.
    6. 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.
    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. 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).
    9. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    10. 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.
    11. 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.
    12. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, September.
    13. 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).
    14. 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.
    15. 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.
    16. Par Sjolander, 2010. "A stationary unbiased finite sample ARCH-LM test procedure," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 1019-1033.
    17. 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.

  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. Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
    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. 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. Felix Chan & Michael McAleer, 2001. "Estimating Smooth Transition Autoregressive Models with GARCH Errors in the Presence of Extreme Observations and Outliers," ISER Discussion Paper 0539, Institute of Social and Economic Research, Osaka University.
    2. Claude Diebolt & Mohamed Chikhi, 2021. "Testing The Weak Form Efficiency Of The French Etf Market With Lstar-Anlstgarch Approach Using A Semiparametric Estimation," Working Papers 09-21, Association Française de Cliométrie (AFC).
    3. Arouri, Mohamed El Hédi & Jawadi, Fredj & Nguyen, Duc Khuong, 2012. "Nonlinearities in carbon spot-futures price relationships during Phase II of the EU ETS," Economic Modelling, Elsevier, vol. 29(3), pages 884-892.
    4. 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.
    5. 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.
    6. 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.
    7. Mohamed Chikhi & Claude Diebolt, 2019. "Testing Nonlinearity through a Logistic Smooth Transition AR Model with Logistic Smooth Transition GARCH Errors," Working Papers of BETA 2019-06, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    8. 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.

  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. 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, 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.
    3. 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.
    4. 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.
    5. 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.
    6. Jacek Kotlowski, 2005. "Money and prices in the Polish economy. Seasonal cointegration approach," Working Papers 20, Department of Applied Econometrics, Warsaw School of Economics.
    7. Justyna Wr'oblewska, 2020. "Bayesian analysis of seasonally cointegrated VAR model," Papers 2012.14820, arXiv.org, revised Apr 2021.
    8. Gianluca Cubadda, 2001. "Complex Reduced Rank Models For Seasonally Cointegrated Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(4), pages 497-511, September.
    9. 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.
    10. 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.
    11. Johansen, Soren & Schaumburg, Ernst, 1998. "Likelihood analysis of seasonal cointegration," Journal of Econometrics, Elsevier, vol. 88(2), pages 301-339, November.
    12. Lee, Hahn Shik & Siklos, Pierre L., 1997. "The role of seasonality in economic time series reinterpreting money-output causality in U.S. data," International Journal of Forecasting, Elsevier, vol. 13(3), pages 381-391, September.
    13. Seong, Byeongchan, 2009. "Bonferroni correction for seasonal cointegrating ranks," Economics Letters, Elsevier, vol. 103(1), pages 42-44, April.
    14. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    15. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.
    16. 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.
    17. 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.
    18. Reimers, Hans-Eggert, 1997. "Forecasting of seasonal cointegrated processes," International Journal of Forecasting, Elsevier, vol. 13(3), pages 369-380, September.
    19. Robert M. Kunst & Michael Reutter, 2000. "Decisions on Seasonal Unit Roots," CESifo Working Paper Series 286, CESifo.
    20. 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.
    21. Kunst, Robert M., 2009. "A Nonparametric Test for Seasonal Unit Roots," Economics Series 233, Institute for Advanced Studies.

  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. Marius Ooms & Björn de Groot & Siem Jan Koopman, 1999. "Time-Series Modelling of Daily Tax Revenues," Computing in Economics and Finance 1999 312, Society for Computational Economics.

  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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Gilles Dufrénot & Valérie Mignon, 2002. "La cointégration non linéaire : une note méthodologique," Économie et Prévision, Programme National Persée, vol. 155(4), pages 117-137.
    6. 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.

    Cited by:

    1. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    2. 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.
    3. 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.
    4. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(1), pages 113-127, April.
    5. 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.
    6. Michael Arghyrou & Christopher Martin & Costas Milas, 2005. "Non-linear inflationary dynamics: evidence from the UK," Oxford Economic Papers, Oxford University Press, vol. 57(1), pages 51-69, January.
    7. David Guerreiro & Valérie Mignon, 2011. "On price convergence in Eurozone," Working Papers hal-04140947, HAL.
    8. Andreas Röthig & Carl Chiarella, 2007. "Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(8), pages 719-737, August.
    9. Carlo Altavilla & Paul De Grauwe, 2010. "Non-linearities in the relation between the exchange rate and its fundamentals," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-21.
    10. 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.
    11. Simeon Coleman & Juan Carlos Cuestas & Estefanía Mourelle, 2011. "Investigating the oil price-exchange rate nexus: Evidence from Africa," Working Papers 2011015, The University of Sheffield, Department of Economics, revised May 2011.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    18. 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.
    19. 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 902, Banco de la Republica de Colombia.
    20. Paolo Gorgi & Siem Jan Koopman, 2020. "Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects," Tinbergen Institute Discussion Papers 20-004/III, Tinbergen Institute.
    21. Jiang, Yu, 2020. "Identification of business cycles and the Great Moderation in the post-war U.S. economy," Economics Letters, Elsevier, vol. 190(C).
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    27. 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).
    28. David Ubilava, 2018. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 239-263.
    29. Emilio Zanetti Chini, 2017. "Generalizing Smooth Transition Autoregressions," DEM Working Papers Series 138, University of Pavia, Department of Economics and Management.
    30. Zhang, Lingxiang, 2013. "Modeling China's inflation dynamics: An MRSTAR approach," Economic Modelling, Elsevier, vol. 31(C), pages 440-446.
    31. 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.
    32. 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.
    33. 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.
    34. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    35. Bec, Frédérique & Bouabdallah, Othman & Ferrara, Laurent, 2014. "The way out of recessions: A forecasting analysis for some Euro area countries," International Journal of Forecasting, Elsevier, vol. 30(3), pages 539-549.
    36. 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.
    37. Goodwin, Barry K. & Holt, Matthew T. & Prestemon, Jeffery P., 2008. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," MPRA Paper 9684, University Library of Munich, Germany.
    38. Gilles Dufrénot & Valérie Mignon & Anne Peguin-Feissolle, 2004. "Business Cycles Asymmetry and Monetary Policy: A Further Investigation using MRSTAR Models," Post-Print halshs-00390154, HAL.
    39. 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.
    40. Di Caro, Paolo, 2014. "Testing and explaining economic resilience with an application to Italian regions," MPRA Paper 60298, University Library of Munich, Germany.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    49. 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.
    50. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, vol. 27(5), pages 1103-1115, September.
    51. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, University Library of Munich, Germany, revised 05 Aug 2005.
    52. 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.
    53. 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.
    54. 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.
    55. Gilles Dufrénot & Valérie Mignon, 2002. "La cointégration non linéaire : une note méthodologique," Économie et Prévision, Programme National Persée, vol. 155(4), pages 117-137.
    56. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
    57. 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.
    58. 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.
    59. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    60. 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.
    61. Lof, Matthijs, 2010. "Heterogeneity in Stock Pricing: A STAR Model with Multivariate Transition Functions," MPRA Paper 30520, University Library of Munich, Germany.
    62. 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.
    63. 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.
    64. 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.
    65. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    66. 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.
    67. 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.
    68. 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.
    69. 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.
    70. 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.
    71. Andreas Röthig, 2009. "Microeconomic Risk Management and Macroeconomic Stability," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-01565-6, October.
    72. Cheng, Xu, 2015. "Robust inference in nonlinear models with mixed identification strength," Journal of Econometrics, Elsevier, vol. 189(1), pages 207-228.
    73. 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.
    74. 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.
    75. 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.
    76. 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.

  170. 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.

    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. 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.
    3. 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.

  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, André, 1997. "A note on optimal estimation from a risk management perspective under possibly mis-specified tail behavior," Serie Research Memoranda 0056, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    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. 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.
    2. 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.
    3. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
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    11. 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.
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    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. 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.
    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. 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.
    5. Paulo M.M. Rodrigues & A.M. Robert Taylor, 2006. "Efficient Tests of the Seasonal Unit Root Hypothesis," Discussion Papers 06/12, University of Nottingham, School of Economics.
    6. 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.
    7. Hassler, Uwe & Rodrigues, Paulo M. M., 2002. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 37696, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Haldrup, Niels Prof. & Montanes, Antonio & Sansó, Andreu, 2000. "Measurement Errors and Outliers in Seasonal Unit Root Testing," University of California at San Diego, Economics Working Paper Series qt0gw7q9hk, Department of Economics, UC San Diego.
    9. 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.
    10. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Shin, Dong Wan, 2004. "Estimation of spectral density for seasonal time series models," Statistics & Probability Letters, Elsevier, vol. 67(2), pages 149-159, April.
    16. 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.
    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. 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.
    19. Bauer, Dietmar, 2019. "Periodic and seasonal (co-)integration in the state space framework," Economics Letters, Elsevier, vol. 174(C), pages 165-168.

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    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    7. Shelley, Gary L. & Wallace, Frederick H., 2011. "Further evidence regarding nonlinear trend reversion of real GDP and the CPI," Economics Letters, Elsevier, vol. 112(1), pages 56-59, July.
    8. 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.
    9. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    10. Maki, Daiki, 2015. "Wild bootstrap testing for cointegration in an ESTAR error correction model," Economic Modelling, Elsevier, vol. 47(C), pages 292-298.
    11. Ben Cheikh, Nidhaleddine & Ben Naceur, Sami & Kanaan, Oussama & Rault, Christophe, 2020. "Investigating the Asymmetric Impact of Oil Prices on GCC Stock Markets," IZA Discussion Papers 13853, Institute of Labor Economics (IZA).
    12. Jesús Otero & Jeremy Smith, 2005. "The KPSS Test with Outliers," Computational Economics, Springer;Society for Computational Economics, vol. 26(3), pages 59-67, November.
    13. 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.
    14. 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.
    15. Yamin Ahmad & Stuart Glosser, 2007. "Searching for Nonlinearities in Real Exchange Rates?," Working Papers 09-01, UW-Whitewater, Department of Economics, revised Jan 2009.
    16. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    17. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    18. 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.
    19. Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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).
    25. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    26. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    27. Franchi, Massimo & Ordóñez, Javier, 2011. "Multiple equilibria in Spanish unemployment," Structural Change and Economic Dynamics, Elsevier, vol. 22(1), pages 71-80, February.
    28. 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].
    29. M Sensier & D R Osborn & N Öcal, 2002. "Asymmetric Interest Rate Effects for the UK Real Economy," Centre for Growth and Business Cycle Research Discussion Paper Series 10, Economics, The University of Manchester.
    30. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    31. Hirsch, Tristan & Rinke, Saskia, 2017. "Changes in Persistence in Outlier Contaminated Time Series," Hannover Economic Papers (HEP) dp-583, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    32. Arghyrou, Michael G. & Gregoriou, Andros, 2008. "Non-linearity versus non-normality in real exchange rate dynamics," Economics Letters, Elsevier, vol. 100(2), pages 200-203, August.
    33. Daiki Maki & Yasushi Ota, 2019. "Testing for time-varying properties under misspecified conditional mean and variance," Papers 1907.12107, arXiv.org, revised Aug 2019.
    34. Arghyrou, Michael G & Gregoriou, Andros & Kontonikas, Alexandros, 2007. "Do real interest rates converge? Evidence from the European Union," Cardiff Economics Working Papers E2007/26, Cardiff University, Cardiff Business School, Economics Section.
    35. 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.
    36. 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.
    37. Zhou, Jian, 2016. "A high-frequency analysis of the interactions between REIT return and volatility," Economic Modelling, Elsevier, vol. 56(C), pages 102-108.
    38. 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.
    39. Arghyrou, Michael G. & Gregoriou, Andros, 2007. "Testing for Purchasing Power Parity correcting for non-normality using the wild bootstrap," Economics Letters, Elsevier, vol. 95(2), pages 285-290, May.
    40. 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.
    41. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    42. Heravi, Saeed & Osborn, Denise R. & Birchenhall, C. R., 2004. "Linear versus neural network forecasts for European industrial production series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 435-446.
    43. 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.
    44. Paolo Giordani, 2006. "A cautionary note on outlier robust estimation of threshold models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 37-47.
    45. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. López Villavicencio, Antonia, 2008. "Nonlinearities or outliers in real exchange rates?," Economic Modelling, Elsevier, vol. 25(4), pages 714-730, July.
    51. 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.
    52. 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.
    53. 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).
    54. 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.
    55. Hina, Hafsa & Qayyum, Abdul, 2015. "Exchange Rate Determination and Out of Sample Forecasting: Cointegration Analysis," MPRA Paper 61997, University Library of Munich, Germany.
    56. 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.
    57. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.

  176. Ariño, M.A. & Franses, Ph.H.B.F., 1996. "Forecasting the Levels of Vector Autoregressive Log-Transformed Time Series," Econometric Institute Research Papers EI 9669-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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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. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    3. 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.
    4. Fok, Dennis & Franses, Philip Hans, 2001. "Forecasting market shares from models for sales," International Journal of Forecasting, Elsevier, vol. 17(1), pages 121-128.
    5. 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.
    6. 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.
    7. 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.
    8. Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
    9. 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).
    10. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    11. 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.
    12. 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.
    13. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    14. Gunnar Bårdsen & Helmut Lütkepohl, 2009. "Forecasting Levels of log Variables in Vector Autoregressions," Working Paper Series 10409, Department of Economics, Norwegian University of Science and Technology.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.

  177. 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.

    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. Hassler, Uwe & Rodrigues, Paulo M. M., 2002. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 37696, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Raimundo Soto, 2000. "Ajuste Estacional e Integración en Variables Macroeconómicas," Working Papers Central Bank of Chile 73, Central Bank of Chile.
    4. 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.
    5. Mickael Salabasis & Sune Karlsson, 2004. "Seasonality, Cycles and Unit Roots," Econometric Society 2004 Australasian Meetings 268, Econometric Society.
    6. Artur C. B. da Silva Lopes & Antonio Montanes, 2005. "The Behavior Of Hegy Tests For Quarterly Time Series With Seasonal Mean Shifts," Econometric Reviews, Taylor & Francis Journals, vol. 24(1), pages 83-108.
    7. 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.
    8. 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.
    9. Lawrence J. Christiano & Richard M. Todd, 2000. "The Conventional Treatment of Seasonality in Business Cycle Analysis: Does it Create Distortions?," NBER Technical Working Papers 0266, National Bureau of Economic Research, Inc.
    10. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    11. Rolando Gonzales Martínez, 2012. "Baysian seasonal analysis with robust priors," Investigación & Desarrollo, Universidad Privada Boliviana, vol. 1(1), pages 88-93.
    12. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    13. 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.

  178. Breitung, J. & Franses, P., 1995. "Impulse Response Functions for Periodic Integration," SFB 373 Discussion Papers 1995,43, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

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

  179. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Papers 9510, Tilburg - Center for Economic Research.

    Cited by:

    1. Clements, Michael & Smith, Jeremy, 1997. "Forecasting Seasonal Uk Consumption Components," Economic Research Papers 268761, University of Warwick - Department of Economics.
    2. Smith, Jeremy & Otero, Jesus, 1997. "Structural breaks and seasonal integration," Economics Letters, Elsevier, vol. 56(1), pages 13-19, September.
    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.

    Cited by:

    1. 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".
    2. 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.
    3. John Board & Charles Sutcliffe & Stephen Wells, 2002. "Transparency and Fragmentation," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-4039-0707-3, March.

  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. Tilak Abeysinghe & Gulasekaran Rajaguru, 2004. "Temporal aggregation, causality distortions and a sign rule," Econometric Society 2004 Australasian Meetings 73, Econometric Society.
    3. 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.
    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.

    Cited by:

    1. 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.
    2. Bildirici, Melike E. & Turkmen, Ceren, 2015. "Nonlinear causality between oil and precious metals," Resources Policy, Elsevier, vol. 46(P2), pages 202-211.
    3. 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.
    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. 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.
    6. Varela, Oscar, 1999. "Futures and realized cash or settle prices for gold, silver, and copper," Review of Financial Economics, Elsevier, vol. 8(2), pages 121-138.
    7. 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).
    8. 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.
    9. 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. Sørensen, Nils Karl, 2002. "Modelling and seasonal forecasting of monthly hotel nights in Denmark," ERSA conference papers ersa02p114, European Regional Science Association.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Hampel, Katharina & Kunz, Marcus & Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2007. "Regional employment forecasts with spatial interdependencies," IAB-Discussion Paper 200702, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. 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.
    8. McErlean, Seamus & Wu, Ziping & Moss, Joan E. & IJpelaar, Jos & Doherty, Andrew, 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 1-19.
    9. Yaovarate Chaovanapoonphol & Christine Lim & Michael McAleer & Aree Wiboonpongse, 2010. "Time Series Modelling of Tourism Demand from the USA, Japan and Malaysia to Thailand," CIRJE F-Series CIRJE-F-722, CIRJE, Faculty of Economics, University of Tokyo.
    10. Otero, Jesus & Smith, Jeremy & Giulietti, Monica, 2008. "Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence," Economic Research Papers 269863, University of Warwick - Department of Economics.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Antonio Aguirre, 2000. "Testing for seasonal unit roots using monthly data," Textos para Discussão Cedeplar-UFMG td139, Cedeplar, Universidade Federal de Minas Gerais.
    16. 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.
    17. 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.
    18. 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.
    19. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    20. 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.
    21. Ankamah-Yeboah, Isaac, 2012. "Spatial Price Transmission in the Regional Maize Markets in Ghana," MPRA Paper 49720, University Library of Munich, Germany.
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    23. 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.
    24. 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.
    25. Ghazanchyan, Manuk, 2014. "Unraveling the Monetary Policy Transmission Mechanism in Sri Lanka," MPRA Paper 59444, University Library of Munich, Germany.
    26. 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.
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    29. 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.
    30. 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.
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    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. Guy Melard & Jean-Michel Pasteels, 1998. "User's manual of Time Series Expert: TSE version 2.3," ULB Institutional Repository 2013/14082, ULB -- Universite Libre de Bruxelles.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. Atle Oglend & Frank Asche, 2016. "Cyclical non-stationarity in commodity prices," Empirical Economics, Springer, vol. 51(4), pages 1465-1479, December.
    44. 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).
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. Guillotreau Patrice & Frédéric Lantz & Lesya Nadzon & Jonathan Rault & Olivier Maury, 2023. "Price Transmission between Energy and Fish Markets: Are Oil Rates Good Predictors of Tuna Prices? [Transmission des prix entre les marchés de l'énergie et du poisson : est-ce que les cours du pétro," Post-Print hal-03948692, HAL.
    50. 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).
    51. 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.
    52. Nakuja, T. & Kerr, William A., 2013. "Protectionism or Legitimate Regulations: What can Trade Partners Expect from the New US Food Safety Regime?," Commissioned Papers 165920, Canadian Agricultural Trade Policy Research Network.
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    55. 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.
    56. 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.
    57. 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.
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    59. 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).
    60. Nasir Hamid Rao & Syed Kalim Hyder Bukhari & Abdul Jalil, 2011. "Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited," Working Papers id:4290, eSocialSciences.
    61. Julio César Alonso & Paul Seeman, 2010. "Prueba de HEGY en R: Una guía," Apuntes de Economía 9098, Universidad Icesi.
    62. 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.
    63. 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.
    64. 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.
    65. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, December.
    66. 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).
    67. 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.
    68. 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.

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

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Díaz-Emparanza Herrero, Ignacio, 2011. "Numerical Distribution Functions for Seasonal Unit Root Tests," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    5. 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.
    6. 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.
    7. 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.
    8. Tiwari, Aviral Kumar & Dutta, Subhendu & Dash, Aruna Kumar, 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), December.
    9. 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.
    10. 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.
    11. 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.
    12. Tiwari, Aviral, 2010. "Is trade deficit sustainable in India? An inquiry," MPRA Paper 24451, University Library of Munich, Germany.
    13. 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.
    14. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
    15. 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.
    16. 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.
    17. Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2009. "Inflation Volatility: An Asian Perspective," MPRA Paper 19489, University Library of Munich, Germany.
    18. 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.
    19. Franses, P. H., 1990. "Seasonality, Outliers And Linearity," Econometric Institute Archives 272395, Erasmus University Rotterdam.
    20. 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.
    21. 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.
    22. 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.

  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. 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.
    3. 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.
    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 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.

  5. 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. Tatsuru Kikuchi & Toranosuke Onishi & Kenichi Ueda, 2021. "Price Stability of Cryptocurrencies as a Medium of Exchange," Papers 2111.08390, arXiv.org.
    2. 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.
    3. Mattera, Raffaele & Franses, Philip Hans, 2023. "Are African business cycles synchronized? Evidence from spatio-temporal modeling," Economic Modelling, Elsevier, vol. 128(C).
    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. 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).
    6. 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. 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.

  6. 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.

  7. 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.

  8. 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.
  9. 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.
  10. 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. 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.
    2. 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.
    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).

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

    Cited by:

    1. Ooft, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    2. 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.

  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.

    Cited by:

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

  13. 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.
  14. 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.

  15. 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.

  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.

  22. 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.
  23. 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.

  24. 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. Francesco Lisi & Ismail Shah, 2024. "Joint Component Estimation for Electricity Price Forecasting Using Functional Models," Energies, MDPI, vol. 17(14), pages 1-18, July.
    2. Monika Zimmermann & Florian Ziel, 2024. "Efficient mid-term forecasting of hourly electricity load using generalized additive models," Papers 2405.17070, arXiv.org.
    3. 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.
    4. 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.
    5. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    6. 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.
    7. 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).
    8. 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).
    9. Jiangwei Liu & Xiaohong Huang, 2021. "Forecasting Crude Oil Price Using Event Extraction," Papers 2111.09111, arXiv.org.
    10. 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.
    11. 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.
    12. 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.
    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. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    15. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    16. 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.
    17. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
    18. 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.
    19. 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.
    20. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
    21. Rostami-Tabar, Bahman & Ziel, Florian, 2022. "Anticipating special events in Emergency Department forecasting," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1197-1213.
    22. 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.
    23. 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.
    24. David BENATIA, 2020. "Reaching New Lows? The Pandemic's Consequences for Electricity Markets," Working Papers 2020-12, Center for Research in Economics and Statistics.
    25. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    26. Jens Kley-Holsteg & Florian Ziel, 2020. "Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso," Papers 2005.04522, arXiv.org.
    27. 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).

  25. 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. 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.
    3. 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.

  26. 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.
  27. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. Francesco Billari & Valentina Rotondi & Jenny Trinitapoli, 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.
    15. 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.

  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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. Elisa Darriet & Marianne Guille & Jean-Christophe Vergnaud & Mariko Shimizu, 2020. "Money illusion, financial literacy and numeracy: experimental evidence," Post-Print hal-02310038, HAL.
    2. Tyran, Jean-Robert & Thomas, Thomas, 2016. "Money Illusion and Household Finance," CEPR Discussion Papers 11643, C.E.P.R. Discussion Papers.
    3. Murota, Ryu-ichiro, 2019. "Negative interest rate policy in a permanent liquidity trap," MPRA Paper 93498, University Library of Munich, Germany.
    4. Lechthaler, Wolfgang & Mileva, Mariya, 2024. "Trade liberalization, wage inequality, and monetary policy," Journal of International Money and Finance, Elsevier, vol. 143(C).
    5. Ryu‐ichiro Murota, 2018. "Aggregate demand deficiency, labor unions, and long‐run stagnation," Metroeconomica, Wiley Blackwell, vol. 69(4), pages 868-888, November.

  35. 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.
  36. 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.
  37. 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.
  38. 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. Tom Coupé, 2022. "Who is the most sought‐after economist? Ranking economists using Google Trends," Southern Economic Journal, John Wiley & Sons, vol. 89(2), pages 611-642, October.
    3. 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).
    4. 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.
    5. Wohlrabe, Klaus & Friedrich, Elisabeth, 2016. "Ordinal ranking aggregation in bibliometric analysis," MPRA Paper 69144, University Library of Munich, Germany.
    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.

  39. 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.
  40. 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. Michael McAleer & Les Oxley & Felix Chan, 2013. "Modelling and Simulation: An Overview," Documentos de Trabajo del ICAE 2013-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    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. 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.

  41. 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.
  42. 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. 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.
    2. 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.
    3. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    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. 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.
    10. 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.
    11. 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.
    12. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.

  43. 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.
  44. 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.
  45. 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.
  46. 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," Economics Letters, Elsevier, vol. 213(C).

  47. 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.
  48. 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.
  49. 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.
  50. 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. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. Schot, Johan & Kanger, Laur, 2018. "Deep transitions: Emergence, acceleration, stabilization and directionality," Research Policy, Elsevier, vol. 47(6), pages 1045-1059.
    7. 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.
    8. 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).
    9. 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.
    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.

  51. 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. Kosse, Anneke, 2013. "Do newspaper articles on card fraud affect debit card usage?," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5382-5391.
    2. 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.
    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. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.
    5. 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.

  52. 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. 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.
    2. 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.
    3. 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.
    4. Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. 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.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    7. 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.
    8. Philip Hans Franses & Bert Bruijn, 2017. "Benchmarking Judgmentally Adjusted Forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 3-11, January.
    9. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2011. "Evaluating Individual and Mean Non-Replicable Forecasts," KIER Working Papers 773, Kyoto University, Institute of Economic Research.
    10. 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.
    11. 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.
    12. Didier Nibbering & Richard Paap & Michel van der Wel, 2015. "What Do Professional Forecasters Actually Predict?," Tinbergen Institute Discussion Papers 15-095/III, Tinbergen Institute, revised 13 Oct 2017.
    13. 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.
    14. 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.
    15. Volha Audzei, 2016. "Confidence Cycles and Liquidity Hoarding," Working Papers 2016/07, Czech National Bank.
    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. 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.
    18. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
    19. 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.

  53. 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.
  54. 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. Theocharis, Zoe & Harvey, Nigel, 2016. "Order effects in judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 32(1), pages 44-60.
    2. 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.
    3. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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. 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.

  55. 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.
  56. 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.
  57. 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.

  58. 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.
  59. 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.
  60. 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. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    7. 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.
    8. 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.
    9. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    10. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2011. "Evaluating Individual and Mean Non-Replicable Forecasts," KIER Working Papers 773, Kyoto University, Institute of Economic Research.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Didier Nibbering & Richard Paap & Michel van der Wel, 2015. "What Do Professional Forecasters Actually Predict?," Tinbergen Institute Discussion Papers 15-095/III, Tinbergen Institute, revised 13 Oct 2017.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. Trapero, Juan R. & Kourentzes, N. & Fildes, R., 2012. "Impact of information exchange on supplier forecasting performance," Omega, Elsevier, vol. 40(6), pages 738-747.
    25. 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.
    26. 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.
    27. 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.
    28. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
    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. 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.
    31. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.

  61. 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.
  62. 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. 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.

  63. 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.

  64. 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. 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.
    3. 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).
    4. 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.

  65. 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.
  66. 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. 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.
    3. Semieniuk, Gregor, 2024. "Inconsistent definitions of GDP: Implications for estimates of decoupling," Ecological Economics, Elsevier, vol. 215(C).

  67. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Madhavan Parthasarathy & Walfried Lassar, 2023. "The adoption and disadoption of electric vehicles by innovators," Marketing Letters, Springer, vol. 34(4), pages 549-573, December.
    10. 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).
    11. 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.
    12. 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.
    13. Donald R. Lehmann & Jeffrey R. Parker, 2017. "Disadoption," AMS Review, Springer;Academy of Marketing Science, vol. 7(1), pages 36-51, June.
    14. 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.
    15. 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.
    16. 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.

  68. 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.

  69. 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.
  70. 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.
  71. 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.
  72. 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. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.
    2. 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.
    3. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Documentos de Trabajo del ICAE 2013-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CARF F-Series CARF-F-219, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    10. 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.
    11. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    12. 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.
    13. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    14. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    17. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
    18. Hafner, Christian M. & Reznikova, Olga, 2012. "On the estimation of dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3533-3545.
    19. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    20. 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.
    21. 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.
    22. 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).
    23. 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.
    24. 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".
    25. 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.
    26. Mahan Tahvildari, 2021. "Forward indifference valuation and hedging of basis risk under partial information," Papers 2101.00251, arXiv.org.
    27. 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.
    28. Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Working Papers in Economics 11/23, University of Canterbury, Department of Economics and Finance.
    29. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.
    30. 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.
    31. 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.
    32. 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.
    33. Fresoli, Diego Eduardo, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    34. 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.
    35. 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.
    36. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    37. 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.
    38. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    39. 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.
    40. 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.
    41. 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.
    42. Bauwens, Luc & Grigoryeva, Lyudmila & Ortega, Juan-Pablo, 2016. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 17-36.
    43. 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.

  73. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    15. 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.
    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. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    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. 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.
    25. 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.
    26. 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.
    27. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
    28. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.
    29. 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.
    30. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.
    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.

  74. 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.

  75. 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.
  76. 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.
  77. 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. 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.
    2. 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.
    3. 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.
    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. 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. 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.
    7. 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.
    8. 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.

  78. 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. 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).
    2. 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.
    3. Dongming Zhu & John W. Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
    4. Veronika Czellar & David T. Frazier & Eric Renault, 2020. "Approximate Maximum Likelihood for Complex Structural Models," Papers 2006.10245, arXiv.org.
    5. 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.
    6. 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.
    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.

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

    Cited by:

    1. 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.
    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. 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).
    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. 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.
    6. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
    7. 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.
    8. 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.
    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.

  80. 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. 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.
    2. Scheiblecker, Marcus, 2013. "Between cointegration and multicointegration: Modelling time series dynamics by cumulative error correction models," Economic Modelling, Elsevier, vol. 31(C), pages 511-517.
    3. Marcus Scheiblecker, 2012. "Modelling Short-run Money Demand for the USA," WIFO Working Papers 442, WIFO.
    4. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.
    5. 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.
    6. 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.

  81. 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.
  82. 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. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. 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).
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.

  83. 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. 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.
    2. E Pavlidis & I Paya & D Peel, 2009. "Real Exchange Rates and Time-Varying Trade Costs," Working Papers 600537, Lancaster University Management School, Economics Department.
    3. 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).
    4. Franchi, Massimo & Ordóñez, Javier, 2011. "Multiple equilibria in Spanish unemployment," Structural Change and Economic Dynamics, Elsevier, vol. 22(1), pages 71-80, February.
    5. Fanelli, Luca & Paruolo, Paolo, 2007. "Speed of Adjustment in Cointegrated Systems," MPRA Paper 9174, University Library of Munich, Germany.
    6. Efthymios Pavlidis & Nicos Pavlidis, 2012. "Dynamic Estimation of Trade Costs from Real Exchange Rates," Working Papers 21883757, Lancaster University Management School, Economics Department.
    7. Strohsal, Till & Winkelmann, Lars, 2015. "Assessing the anchoring of inflation expectations," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 33-48.
    8. Frédéric Karamé, 2015. "Asymmetries and Markov-switching structural VAR," Post-Print hal-02296101, HAL.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.

  84. 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.
  85. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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).
    22. 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.
    23. 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).
    24. 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.
    25. 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.
    26. 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.
    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. 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.
    30. 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.
    31. 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.
    32. 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.
    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.

  86. 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, 2010. "Multi-horizon inflation forecasts using disaggregated data," Economic Modelling, Elsevier, vol. 27(3), pages 666-677, May.
    2. 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.

  87. 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. Dimson, Elroy & Spaenjers, Christophe, 2011. "Ex post: The investment performance of collectible stamps," Journal of Financial Economics, Elsevier, vol. 100(2), pages 443-458, May.
    2. Spaenjers, C., 2011. "Essays in alternative investments," Other publications TiSEM 8c51041f-6a63-451f-b7f4-8, Tilburg University, School of Economics and Management.

  88. 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. 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.
    2. Herrerias, M.J., 2013. "Seasonal anomalies in electricity intensity across Chinese regions," Applied Energy, Elsevier, vol. 112(C), pages 1548-1557.

  89. 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.
  90. 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. Maarten Dossche & Freddy Heylen & Dirk Van den Poel, 2006. "The kinked demand curve and price rigidity : evidence from scanner data," Working Paper Research 99, National Bank of Belgium.
    2. 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.
    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. 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.
    5. 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.
    6. 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.
    7. Macé, Sandrine, 2012. "The Impact and Determinants of Nine-Ending Pricing in Grocery Retailing," Journal of Retailing, Elsevier, vol. 88(1), pages 115-130.
    8. 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.
    9. Otto, Philipp E. & Schmidt, Lennard, 2021. "Reservation price uncertainty: Loss, virtue, or emotional heterogeneity?," Journal of Economic Psychology, Elsevier, vol. 87(C).
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Ngobo, Paul Valentin, 2011. "What Drives Household Choice of Organic Products in Grocery Stores?," Journal of Retailing, Elsevier, vol. 87(1), pages 90-100.
    17. Michael Löffler, 2015. "Measuring willingness to pay: do direct methods work for premium durables?," Marketing Letters, Springer, vol. 26(4), pages 535-548, December.
    18. 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.
    19. 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.
    20. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2008. "Modeling the Effectiveness of Hourly Direct-Response Radio Commercials," ERIM Report Series Research in Management ERS-2008-019-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.
    21. 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.
    22. Jean-Pierre H. Dubé, 2018. "Microeconometric Models of Consumer Demand," NBER Working Papers 25215, National Bureau of Economic Research, Inc.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. Richards, Timothy J. & Gómez, Miguel I. & Printezis, Iryna, 2014. "Hysteresis, Price Acceptance, and Reference Prices," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 164872, Agricultural and Applied Economics Association.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. Nicole Koschate-Fischer & Katharina Wüllner, 2017. "New developments in behavioral pricing research," Journal of Business Economics, Springer, vol. 87(6), pages 809-875, August.
    38. 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.
    39. 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).
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.

  91. 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.
  92. 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.
  93. 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.
  94. 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.
  95. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    11. 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.
    12. 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.
    13. 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.
    14. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Hee Mok Park & Joseph Pancras, 2022. "Social and Spatiotemporal Impacts of Casino Jackpot Events," Marketing Science, INFORMS, vol. 41(3), pages 575-592, May.
    21. 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.
    22. 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.
    23. Ashwin Aravindakshan & Prasad A. Naik, 2015. "Understanding the Memory Effects in Pulsing Advertising," Operations Research, INFORMS, vol. 63(1), pages 35-47, February.
    24. 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).
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.

  96. 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.
    See citations under working paper version above.
  97. 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. 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.
    2. Dominique Guegan, 2007. "Global and local stationary modelling in finance: theory and empirical evidence," Post-Print halshs-00187875, HAL.
    3. Dominique Guegan, 2008. "Non-stationarity and meta-distribution," Post-Print halshs-00270708, 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. Dominique Guegan & Zhiping Lu, 2007. "A note on self-similarity for discrete time series," Post-Print halshs-00187910, HAL.

  98. 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. 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.
    2. 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.
    3. Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
    4. 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.
    5. 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.
    6. 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.
    7. Willem P Sijp & Anastasios Panagiotelis, 2024. "Estimating granular house price distributions in the Australian market using Gaussian mixtures," Papers 2404.05178, arXiv.org.
    8. 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.
    9. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
    10. 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.
    11. 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.
    12. Ord, Keith, 2007. "Comments on "significance tests harm progress in forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 331-332.
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    16. 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.
    17. 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.
    18. 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.
    19. 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).
    20. Armstrong, J. Scott, 2007. "Significance Tests Harm Progress in Forecasting," MPRA Paper 81664, University Library of Munich, Germany.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. Kourentzes, Nikolaos, 2014. "On intermittent demand model optimisation and selection," International Journal of Production Economics, Elsevier, vol. 156(C), pages 180-190.
    28. Zhang, Bohan & Panagiotelis, Anastasios & Kang, Yanfei, 2024. "Discrete forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 318(1), pages 143-153.
    29. 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.
    30. 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).
    31. 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.
    32. 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, July.
    33. 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).
    34. 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.
    35. Bergmeir, Christoph & Hyndman, Rob J. & Benítez, José M., 2016. "Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation," International Journal of Forecasting, Elsevier, vol. 32(2), pages 303-312.
    36. 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.
    37. Stekler, H.O., 2007. "Significance tests harm progress in forecasting: Comment," International Journal of Forecasting, Elsevier, vol. 23(2), pages 329-330.
    38. 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.
    39. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
    40. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    41. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. Davide Provenzano & Serena Volo, 2022. "Tourism recovery amid COVID-19: The case of Lombardy, Italy," Tourism Economics, , vol. 28(1), pages 110-130, February.
    48. 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.
    49. 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.
    50. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. 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.
    56. 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.
    57. 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.
    58. 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.

  99. 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. 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.
    2. Owen, Ann L. & Temesvary, Judit, 2012. "Foreign lending, local lending, and economic growth," MPRA Paper 39978, University Library of Munich, Germany.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. 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.
    11. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Castellacci, Fulvio, 2008. "Technology clubs, technology gaps and growth trajectories," MPRA Paper 27595, University Library of Munich, Germany.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Yuki, Kazuhiro, 2012. "Education, inequality, and development in a dual economy," MPRA Paper 39062, University Library of Munich, Germany.
    22. Davis, Lewis & Owen, Ann L. & Videras, Julio, 2007. "Do all countries follow the same growth process?," MPRA Paper 11589, University Library of Munich, Germany, revised Sep 2008.
    23. Owen, Ann L. & Videras, Julio, 2012. "The quality of growth," MPRA Paper 38342, University Library of Munich, Germany.
    24. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.
    25. Michele Battisti & Christopher F. Parmeter, 2011. "Income Polarization, Convergence Tools and Mixture Analysis," Working Papers 2011-17, University of Miami, Department of Economics.
    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. Leonardo Becchetti & Luisa Corrado & Fiammetta Rossetti, 2008. "Easterlin-types and Frustrated Achievers: the Heterogeneous E¤ects of Income Changes on Life Satisfaction," CEIS Research Paper 127, Tor Vergata University, CEIS, revised 09 Sep 2008.
    28. Tim Salimans, 2011. "Variable Selection and Functional Form Uncertainty in Cross-Country Growth Regressions," Tinbergen Institute Discussion Papers 11-012/4, Tinbergen Institute.
    29. 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.
    30. 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.
    31. 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.
    32. Di Vaio, Gianfranco & Enflo, Kerstin, 2011. "Did globalization drive convergence? Identifying cross-country growth regimes in the long run," European Economic Review, Elsevier, vol. 55(6), pages 832-844, August.
    33. Michele Battisti & Christopher F. Parmeter, 2010. "Convergence Tools and Mixture Analysis," Working Papers CELEG 1007, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. Rosa Bernardini Papalia & Silvia Bertarelli, 2013. "Nonlinearities in economic growth and club convergence," Empirical Economics, Springer, vol. 44(3), pages 1171-1202, June.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. Arye Hillman, 2007. "Economic and security consequences of supreme values," Public Choice, Springer, vol. 131(3), pages 259-280, June.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    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.

  100. 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.
  101. 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.
  102. 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.

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    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.

  103. 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.

  104. 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.
  105. 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.

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    1. 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.
    2. 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].
    3. 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).
    4. 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.
    5. Lee, Kevin & Shields, Kalvinder K., 2011. "Decision-making in hard times: What is a recession, why do we care and how do we know when we are in one?," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 43-60, January.
    6. 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).

  106. 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.
    See citations under working paper version above.
  107. 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.
    See citations under working paper version above.
  108. 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. Hermann Ndoya hegueu & Aristophane Djeufack dongmo, 2021. "Urbanization, Governance and Informal Economy: an African Tale," Economics Bulletin, AccessEcon, vol. 41(3), pages 1525-1540.
    2. Cristina Jude & Gregory Levieuge, 2017. "Growth Effect of Foreign Direct Investment in Developing Economies: The Role of Institutional Quality," The World Economy, Wiley Blackwell, vol. 40(4), pages 715-742, April.
    3. JUDE, Cristina & LEVIEUGE, Gregory, 2013. "Growth effect of FDI in developing economies: The role of institutional quality," MPRA Paper 49321, University Library of Munich, Germany.
    4. Davide Furceri & Mr. Prakash Loungani, 2015. "Capital Account Liberalization and Inequality," IMF Working Papers 2015/243, International Monetary Fund.
    5. 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.
    6. 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.
    7. Juan Carlos Cuestas & Estefania Mourelle & Paulo José Regis, 2019. "Real exchange rate misalignments in CEECs: have they hindered growth?," Bank of Estonia Working Papers wp2018-05, Bank of Estonia, revised 23 Jan 2019.
    8. Damette, Olivier & Seghir, Majda, 2018. "Natural resource curse in oil exporting countries: A nonlinear approach," International Economics, Elsevier, vol. 156(C), pages 231-246.
    9. 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).
    10. 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.
    11. 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.
    12. 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.
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    41. 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).
    42. 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.
    43. Jude Eggoh & Chrysost Bangake & Gervasio Semedo, 2018. "Do remittances spur economic growth? Evidence from developing countries," Post-Print hal-02107277, HAL.
    44. 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.
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    51. Wafa Ghardallou & Abdelkader Boudriga, 2014. "Financial Development and Democracy: is the Relationship Non-Linear?," Working Papers 886, Economic Research Forum, revised Dec 2014.
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    1. 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.
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    8. 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.
    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. 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.
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    13. 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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      • 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.
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    24. Yongtao Guan, 2008. "A KPSS Test for Stationarity for Spatial Point Processes," Biometrics, The International Biometric Society, vol. 64(3), pages 800-806, September.
    25. 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.
    26. Ghassan, Hassan B. & Alhajhoj, Hassan R. & Balli, Faruk, 2020. "Bi-Demographic and Current Account Dynamics using SVAR Model: Evidence from Saudi Arabia," MPRA Paper 109772, University Library of Munich, Germany, revised Jun 2021.
    27. SBIA, Rashid & Shahbaz, Muhammad & Ozturk, Ilhan, 2016. "Economic Growth, Financial Development, Urbanization and Electricity Consumption Nexus in UAE," MPRA Paper 74790, University Library of Munich, Germany, revised 24 Oct 2016.
    28. 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.
    29. Sephton, Peter & Mann, Janelle, 2018. "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, vol. 71(C), pages 273-281.
    30. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    31. Baum, Christopher F. & Barkoulas, John, 2006. "Dynamics of Intra-EMS Interest Rate Linkages," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(2), pages 469-482, March.
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    33. 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.
    34. 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.
    35. George Kapetanios, 2007. "Testing for Strict Stationarity," Working Papers 602, Queen Mary University of London, School of Economics and Finance.
    36. Jönsson, Kristian, 2006. "Finite-Sample Stability of the KPSS Test," Working Papers 2006:23, Lund University, Department of Economics.
    37. 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.
    38. 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.
    39. 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.
    40. Koch, Cathérine Tahmee, 2014. "Risky adjustments or adjustments to risks: Decomposing bank leverage," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 242-254.
    41. 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.
    42. Sephton, Peter S., 2019. "El Niño, La Niña, and a cup of Joe," Energy Economics, Elsevier, vol. 84(C).
    43. 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).
    44. 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.
    45. Kapetanios, George, 2009. "Testing for strict stationarity in financial variables," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2346-2362, December.
    46. 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.
    47. Lee Kian Lim & Michael McAleer, 2003. "Convergence and Catching Up in ASEAN: A Comparative Analysis," CIRJE F-Series CIRJE-F-218, CIRJE, Faculty of Economics, University of Tokyo.
    48. 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.
    49. Sephton, Peter, 2023. "Threshold cointegration and asymmetries between dividends and earnings news," Finance Research Letters, Elsevier, vol. 58(PB).
    50. 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).
    51. 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.
    52. 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.
    53. Eberhardt, Markus & Teal, Francis, 2009. "A Common Factor Approach to Spatial Heterogeneity in Agricultural Productivity Analysis," MPRA Paper 15810, University Library of Munich, Germany.
    54. 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.
    55. 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).
    56. 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.
    57. 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.
    58. 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.
    59. 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).
    60. 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.
    61. 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.
    62. Lee, Jin & Lee, Young Im, 2012. "Size improvement of the KPSS test using sieve bootstraps," Economics Letters, Elsevier, vol. 116(3), pages 483-486.
    63. 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).
    64. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    65. Sephton, Peter S., 2022. "Revisiting the inflation-hedging properties of precious metals in Africa," Resources Policy, Elsevier, vol. 77(C).
    66. Yilmazkuday, Hakan, 2009. "Inflation Targeting and Inflation Convergence within Turkey," MPRA Paper 16770, University Library of Munich, Germany.
    67. Lyócsa, Štefan & Baumöhl, Eduard, 2012. "Testing the covariance stationarity of CEE stocks," MPRA Paper 43432, University Library of Munich, Germany.
    68. 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.
    69. 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.
    70. 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.
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  111. 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.
  112. 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. 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.
    3. Pär Österholm, 2010. "Improving Unemployment Rate Forecasts Using Survey Data," Finnish Economic Papers, Finnish Economic Association, vol. 23(1), pages 16-26, Spring.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    9. Pincheira, Pablo & Hernández, Ana María, 2019. "Forecasting Unemployment Rates with International Factors," MPRA Paper 97855, University Library of Munich, Germany.
    10. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.
    11. 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.

  113. 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.
  114. 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. 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.
    2. 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.
    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.

  115. 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.

  116. 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. 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.
    3. 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.
    4. 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.
    5. 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.

  117. 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. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    3. 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.
    4. 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.
    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.

  118. 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.

  119. 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.
  120. 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.
  121. 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.
  122. 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.
  123. 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.

  124. 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.
  125. 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.
  126. 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. 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.
    2. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Post-Print halshs-00179285, HAL.
    3. 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.
    4. 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.
    5. 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.
    6. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Long-memory dynamics in a SETAR model - applications to stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 391-406, December.
    7. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. 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.
    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.

  127. 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.
  128. 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.
  129. 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.
  130. 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.
  131. 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. 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.
    2. Shiqing Ling & Michael McAleer & Howell Tong, 2015. "Frontiers in Time Series and Financial Econometrics: An Overview," Documentos de Trabajo del ICAE 2015-04, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. 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).
    4. Caginalp, Carey & Caginalp, Gunduz, 2020. "Derivation of non-classical stochastic price dynamics equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    5. 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.
    6. Carey Caginalp & Gunduz Caginalp, 2019. "Derivation of non-classical stochastic price dynamics equations," Papers 1908.01103, arXiv.org, revised Aug 2020.
    7. 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.
    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. 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.
    10. 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.
    11. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    12. 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.
    13. 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.

  132. 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. 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.
    2. 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.

  133. 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. 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.
    2. 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.
    3. 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.
    4. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: A fractionally integrated SETAR model," Post-Print halshs-00185369, 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. 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.
    7. 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.
    8. 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).
    9. 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.
    10. James D. Hamilton, 2005. "What's real about the business cycle?," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 435-452.
    11. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Post-Print halshs-00179285, HAL.
    12. Christian Peretti, 2007. "Long Memory and Hysteresis," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 363-389, Springer.
    13. 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.
    14. Panagiotidis, Theodore & Pelloni, Gianluigi, 2007. "Nonlinearity In The Canadian And U.S. Labor Markets: Univariate And Multivariate Evidence From A Battery Of Tests," Macroeconomic Dynamics, Cambridge University Press, vol. 11(5), pages 613-637, November.
    15. 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.
    16. Lahiani, A. & Scaillet, O., 2009. "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," International Journal of Forecasting, Elsevier, vol. 25(2), pages 418-428.
    17. 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.
    18. 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.
    19. Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
    20. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2004. "Non-linearities and fractional integration in the US unemployment rate," HWWA Discussion Papers 259, Hamburg Institute of International Economics (HWWA).
    21. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    22. 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.
    23. 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.
    24. Adnen Ben Nasr & Mehmet Balcilar & Ahdi N. Ajmi & Goodness C. Aye & Rangan Gupta & Reneé van Eyden, 2014. "Causality between Inflation and Inflation Uncertainty in South Africa: Evidence from a Markov-Switching Vector Autoregressive Model," Working Papers 201453, University of Pretoria, Department of Economics.
    25. Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil).
    26. M Sensier & D R Osborn & N Öcal, 2002. "Asymmetric Interest Rate Effects for the UK Real Economy," Centre for Growth and Business Cycle Research Discussion Paper Series 10, Economics, The University of Manchester.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. Luis A. Gil-Alana & Guglielmo M. Caporale, 2008. "Modelling the US, the UK and Japanese unemployment rates. Fractional integrationand structural breaks," Faculty Working Papers 11/08, School of Economics and Business Administration, University of Navarra.
    32. Richard T. Baillie & George Kapetanios, 2005. "Testing for Neglected Nonlinearity in Long Memory Models," Working Papers 528, Queen Mary University of London, School of Economics and Finance.
    33. Ralf Becker & Denise R. Osborn, 2012. "Weighted Smooth Transition Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 795-811, August.
    34. 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.
    35. 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.
    36. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2015. "Are Unemployment Rates in OECD Countries Stationary? Evidence from Univariate and Panel Unit Root Tests," IZA Discussion Papers 9571, Institute of Labor Economics (IZA).
    37. Gross, Marco & Binder, Michael, 2013. "Regime-switching global vector autoregressive models," Working Paper Series 1569, European Central Bank.
    38. Kapetanios, George, 2006. "Nonlinear autoregressive models and long memory," Economics Letters, Elsevier, vol. 91(3), pages 360-368, June.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.
    45. Kurt Graden Lunsford, 2023. "Business Cycles and Low-Frequency Fluctuations in the US Unemployment Rate," Working Papers 23-19, Federal Reserve Bank of Cleveland.
    46. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Long-memory dynamics in a SETAR model - applications to stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 391-406, December.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. 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.
    56. 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.
    57. 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.
    58. 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.
    59. 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).
    60. 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.

  134. 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.

  135. 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.
  136. 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.

  137. 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.

  138. 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.
  139. 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. 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.
    2. Koen Decancq & André Decoster & Erik Schokkaert, 2007. "The evolution of World inequality in Well-being," Working Papers of Department of Economics, Leuven ces0704, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    3. Neumayer, Eric, 2003. "Beyond income: convergence in living standards, big time," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 275-296, September.
    4. 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.
    5. Duncan, Roberto & Toledo, Patricia, 2018. "Do overweight and obesity prevalence rates converge in Europe?," Research in Economics, Elsevier, vol. 72(4), pages 482-493.
    6. 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.
    7. Cuffaro, Miranda & Cracolici, Maria Francesca & Nijkamp, Peter, 2007. "Measuring the performance of Italian regions: on social and economic dimensions," Serie Research Memoranda 0013, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    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. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. David Canning, 2012. "Progress in Health around the World," Journal of Development Studies, Taylor & Francis Journals, vol. 48(12), pages 1784-1798, December.
    22. 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.
    23. 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.
    24. Kshamanidhi Adabar, 2004. "Convergence of Standards of Living Across Indian States," Working Papers 153, Institute for Social and Economic Change, Bangalore.
    25. Simplice A, Asongu, 2012. "African Development: Beyond Income Convergence," MPRA Paper 36054, University Library of Munich, Germany.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. Christopher GRIGORIOU, 2008. "Survival Convergence: Specification Matters," Working Papers 200815, CERDI.
    34. 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.
    35. 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).
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    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. Grigoriou, Christopher & Guillaumont, Patrick & Yang, Wenyan, 2005. "Child mortality under Chinese reforms," China Economic Review, Elsevier, vol. 16(4), pages 441-464.
    42. 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.
    43. 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.
    44. 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).

  140. 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.
  141. 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.
  142. 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.
  143. 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.
  144. 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. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2020. "Inference on Semiparametric Multinomial Response Models," Discussion Papers Series 627, School of Economics, University of Queensland, Australia.
    2. 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.
    3. 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.
    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. 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.
    6. 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.
    7. 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.
    8. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    9. 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.
    10. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2008. "Modeling the Effectiveness of Hourly Direct-Response Radio Commercials," ERIM Report Series Research in Management ERS-2008-019-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.
    11. 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.
    12. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.

  145. 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.
  146. 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. 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.
    3. 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.
    4. 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.
    5. Andrea Beltratti & Claudio Morana, 2006. "Comovements in International Stock Markets," ICER Working Papers 3-2006, ICER - International Centre for Economic Research.
    6. Ji, Aiwen & Shang, Pengjian, 2019. "Analysis of financial time series through forbidden patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    7. Natividad Blasco & Pilar Corredor & Sandra Ferreruela, 2009. "Detecting intentional herding: what lies beneath intraday data in the spanish stock market," Documentos de Trabajo dt2009-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    8. 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.
    9. 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.
    10. 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).
    11. Claudio Morana, 2008. "International stock markets comovements: the role of economic and financial integration," Empirical Economics, Springer, vol. 35(2), pages 333-359, September.
    12. 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.

  147. 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.

    Cited by:

    1. 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.
    2. Pesaran, M.H., 2004. "A Pair-wise Approach to Testing for Output and Growth Convergence," Cambridge Working Papers in Economics 0453, Faculty of Economics, University of Cambridge.
    3. Castellacci, Fulvio, 2008. "The technology clubs: the distribution of knowledge across nations," MPRA Paper 27597, University Library of Munich, Germany.
    4. 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.
    5. 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.
    6. Carvalho, Vasco M. & Harvey, Andrew C., 2005. "Growth, cycles and convergence in US regional time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 667-686.
    7. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    8. 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.
    9. 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.
    10. Gwendolyn Aldrich & Kristine Grimsrud & Jennifer Thacher & Matthew Kotchen, 2007. "Relating environmental attitudes and contingent values: how robust are methods for identifying preference heterogeneity?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(4), pages 757-775, August.
    11. 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.
    12. 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.
    13. 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.
    14. Thanasis Stengos & Ege Yazgan & Harun Ozkan, 2016. "Persistence in Convergence: Some further results," Working Papers 1605, University of Guelph, Department of Economics and Finance.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Tirtha Chatterjee & A. Ganesh Kumar, 2014. "Neighborhood and agricultural clusters across states of India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2014-044, Indira Gandhi Institute of Development Research, Mumbai, India.
    20. 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.
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    73. Tommaso Proietti, 2005. "Convergence in Italian regional per-capita GDP," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 497-506.
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    78. Esfandiar Maasoumi & Le Wang, 2008. "Economic Reform, Growth and Convergence in China," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 128-154, March.
    79. Fuat C. Beylunioglu & Thanasis Stengos & Ege Yazgan, 2016. "Detecting Convergence Clubs," Working Papers 1604, University of Guelph, Department of Economics and Finance.
    80. 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.
    81. 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.
    82. 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.
    83. Epstein, Philip & Howlett, Peter & Schulze, Max-Stephan, 2003. "Distribution dynamics: stratification, polarization, and convergence among OECD economies, 1870-1992," Explorations in Economic History, Elsevier, vol. 40(1), pages 78-97, January.
    84. Massimiliano Affinito & Fabio Farabullini, 2009. "Does the Law of One Price Hold in Euro-Area Retail Banking? An Empirical Analysis of Interest Rate Differentials across the Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 5(1), pages 5-37, March.
    85. 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.
    86. 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.
    87. 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.
    88. 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.
    89. 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.
    90. Mariam Camarero & Juana Castillo-Giménez & Andrés Picazo-Tadeo & Cecilio Tamarit, 2014. "Is eco-efficiency in greenhouse gas emissions converging among European Union countries?," Empirical Economics, Springer, vol. 47(1), pages 143-168, August.
    91. 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.
    92. 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.
    93. 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.
    94. Arfat Ahmad Sofi & S. Raja Sethu Durai, 2015. "Club Convergence Across Indian States: An Empirical Analysis," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 40(4), pages 107-124, December.
    95. Hening Liu & Le Wang, 2010. "Time series analysis of income convergence in China," Applied Economics Letters, Taylor & Francis Journals, vol. 17(1), pages 25-29, January.
    96. 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.
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    98. 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.
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  148. 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.
  149. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    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.

  150. 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. Tomas del Barrio Castro & Denise R Osborn, 2005. "Cointegration for Periodically Integrated Processes," Economics Discussion Paper Series 0522, Economics, The University of Manchester.
    2. 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.
    3. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.
    4. 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.
    5. 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.
    6. 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.
    7. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    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. Lawrence J. Christiano & Richard M. Todd, 2000. "The Conventional Treatment of Seasonality in Business Cycle Analysis: Does it Create Distortions?," NBER Technical Working Papers 0266, National Bureau of Economic Research, Inc.
    10. 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.

  151. 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.
  152. 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. 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.
    2. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Thavaneswaran, A. & Appadoo, S.S. & Peiris, S., 2005. "Forecasting volatility," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 1-10, November.
    13. 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.
    14. Amélie Charles & Olivier Darné & Laurent Ferrara, 2014. "Does the Great Recession imply the end of the Great Moderation? International evidence," Working Papers hal-04141344, HAL.
    15. Jurgen A. Doornik & Marius Ooms, 2003. "Multimodality in the GARCH Regression Model," Economics Papers 2003-W20, Economics Group, Nuffield College, University of Oxford.
    16. 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.
    17. 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.
    18. Carnero, María Ángeles, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    19. 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.
    20. 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.
    21. 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.
    22. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    23. Watkins, Clinton & McAleer, Michael, 2005. "Related commodity markets and conditional correlations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 567-579.
    24. 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.
    25. 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.
    26. 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.
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      • 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.
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    49. 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.
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    54. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.
    55. 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.
    56. 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.
    57. 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.
    58. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    59. 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).
    60. 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).
    61. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    62. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    63. 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.
    64. 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.
    65. 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.
    66. 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.
    67. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    68. 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).
    69. 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.
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    76. 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.
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    79. Grané, Aurea & 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.
    80. Mathieu Gatumel & Dominique Guegan, 2008. "Dynamic Analysis of the Insurance Linked Securities Index," Post-Print halshs-00320378, HAL.
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    82. 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.
    83. 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.
    84. 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.
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    86. 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.

  153. 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. Lütkepohl, Helmut & Proietti, Tommaso, 2011. "Does the Box-Cox transformation help in forecasting macroeconomic time series?," Working Papers 08/2011, University of Sydney Business School, Discipline of Business Analytics.
    2. 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.
    3. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    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.

  154. 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.
  155. 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.
  156. 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.
  157. 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. 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.
    2. 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".

  158. 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. 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.
    2. Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Matas Mir, Antonio & Osborn, Denise R, 2004. "Seasonal adjustment and the detection of business cycle phases," Working Paper Series 357, European Central Bank.
    8. 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.
    9. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    10. 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.
    11. Dalibor Stevanovic & Stéphane Surprenant & Rachidi Kotchoni, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.

  159. 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).

  160. 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. 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.
    2. 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.
    3. 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.
    4. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    14. 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.

  161. 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. 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.
    2. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    3. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    4. Holmes, Mark J., 2005. "New Evidence on Long-Run Output Convergence Among Latin American Countries," Journal of Applied Economics, Universidad del CEMA, vol. 8(2), pages 1-21, November.
    5. 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.
    6. Gary Madden & Scott J. Savage, 1998. "Sources of Australian Labour Productivity Change 1950–1994," The Economic Record, The Economic Society of Australia, vol. 74(227), pages 362-372, December.
    7. 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.
    8. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    9. 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.
    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. Héctor Manuel Záarte Solano & Angélica Rengifo Gómez, 2013. "Forecasting annual inflation with power transformations: the case of inflation targeting countries," Borradores de Economia 10462, Banco de la Republica.

  162. 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. 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. 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.
    5. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    6. 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.
    7. 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.
    8. Bernd Schwaab, 2012. "Conditional probabilities and contagion measures for euro area sovereign default risk," Research Bulletin, European Central Bank, vol. 17, pages 6-11.
    9. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    10. 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.
    11. 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.
    12. Diego Winkelried, 2014. "Exchange rate pass-through and inflation targeting in Peru," Empirical Economics, Springer, vol. 46(4), pages 1181-1196, June.
    13. Carlos Andrés Perilla Castro, 2001. "Capitales mínimos de los establecimientos de crédito," Monetaria, CEMLA, vol. 0(3), pages 271-353, julio-sep.
    14. 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.
    15. 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.
    16. Katarzyna Rosiak-Lada, 2008. "Stylized Facts of Macroeconomics: the Polish Experience," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 20.
    17. 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.
    18. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    19. 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.
    20. 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.
    21. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    28. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    29. 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).
    30. 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.
    31. 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.

  163. 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.
  164. 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. 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.
    2. 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.
    3. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    4. 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.
    5. Albertson, Kevin & Aylen, Jonathan, 2003. "Forecasting the behaviour of manufacturing inventory," International Journal of Forecasting, Elsevier, vol. 19(2), pages 299-311.

  165. 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. 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.
    2. 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.
    3. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    4. 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.
    5. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    6. 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.
    7. 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.
    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. 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.
    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.

  166. 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. 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.
    2. 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.
    3. Hassler, Uwe & Rodrigues, Paulo M. M., 2002. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 37696, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Haldrup, Niels Prof. & Montanes, Antonio & Sansó, Andreu, 2000. "Measurement Errors and Outliers in Seasonal Unit Root Testing," University of California at San Diego, Economics Working Paper Series qt0gw7q9hk, Department of Economics, UC San Diego.
    5. 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.
    6. 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.
    7. 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.
    8. Dick van Dijk 1 & Birgit Strikholm & Timo Teräsvirta, 2003. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 79-98, June.
    9. Bolat, Süleyman & Tiwari, Aviral Kumar & Kyophilavong, Phouphet, 2017. "Testing the inflation rates in MENA countries: Evidence from quantile regression approach and seasonal unit root test," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1089-1095.
    10. 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.
    11. Artur C. B. da Silva Lopes & Antonio Montanes, 2005. "The Behavior Of Hegy Tests For Quarterly Time Series With Seasonal Mean Shifts," Econometric Reviews, Taylor & Francis Journals, vol. 24(1), pages 83-108.
    12. 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.
    13. 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).
    14. 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.
    15. 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.
    16. 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.
    17. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    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. 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.
    25. Sun, Jingwei & Shi, Wendong, 2014. "Aggregation of the generalized fractional processes," Economics Letters, Elsevier, vol. 124(2), pages 258-262.
    26. 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.
    27. 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.
    28. 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.

  167. 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. 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.
    3. Diego Winkelried Quezada, 2003. "Indicadores adelantados de la inflación en el Perú," Monetaria, CEMLA, vol. 0(4), pages 345-382, octubre-d.
    4. 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.
    5. 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.
    6. Philip Kostov & John Lingard, 2005. "Seasonally specific model analysis of UK cereals prices," Econometrics 0507014, University Library of Munich, Germany.
    7. Fabio Busetti, 2006. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 419-438, May.
    8. Younes Ben Zaied & Marie-Estelle Binet, 2015. "Modelling seasonality in residential water demand: the case of Tunisia," Post-Print halshs-01102007, HAL.
    9. 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.
    10. 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.
    11. Olivier Darné, 2003. "Maximum likelihood seasonal cointegration tests for daily data," Economics Bulletin, AccessEcon, vol. 3(18), pages 1-8.
    12. Darne, Olivier, 2004. "Seasonal cointegration for monthly data," Economics Letters, Elsevier, vol. 82(3), pages 349-356, March.
    13. 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.
    14. Nikolaos Giannellis & Minoas Koukouritakis, 2011. "Behavioural equilibrium exchange rate and total misalignment: evidence from the euro exchange rate," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 38(4), pages 555-578, November.
    15. 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.
    16. 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.
    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.

  168. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    7. Nathan Lael Joseph, 2003. "Using monthly returns to model conditional heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 791-801.
    8. 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).
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.

  169. 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. Nikola Kutin & Zakaria Moussa & Thomas Vallée, 2018. "Factors behind the Freight Rates in the Liner Shipping Industry," Working Papers halshs-01828633, HAL.
    2. 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).
    3. Roar Adland & Pierre Cariou & Francois-Charles Wolff, 2017. "What makes a freight market index ?," Post-Print hal-03913228, HAL.
    4. 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.
    5. 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.
    6. Haigh, Michael S. & Nomikos, Nikos K. & Bessler, David A., 2002. "Integration And Causality In International Freight Markets--Modeling With Error Correction And Directed Acyclic Graphs," Working Papers 28558, University of Maryland, Department of Agricultural and Resource Economics.
    7. 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.
    8. 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.
    9. 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.
    10. Prochazka, Vit & Adland, Roar & Wallace, Stein W., 2018. "The value of foresight in the drybulk freight market," Discussion Papers 2018/1, Norwegian School of Economics, Department of Business and Management Science.
    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. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    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. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    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. 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.

  170. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    7. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    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. 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.
    14. Bensalma, Ahmed, 2018. "Two Distinct Seasonally Fractionally Differenced Periodic Processes," MPRA Paper 84969, University Library of Munich, Germany.

  171. 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. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    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. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    4. 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.
    5. 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.
    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.

  172. 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.
  173. 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. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    2. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    3. 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.
    4. 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.
    5. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    6. 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.
    7. 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.
    8. 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.
    9. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2010. "Testing Fractional Order of Long Memory Processes: A Monte Carlo Study," PSE-Ecole d'économie de Paris (Postprint) hal-00486655, HAL.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. John Barkoulas & Christopher F. Baum, 2003. "Long-Memory Forecasting of U.S. Monetary Indices," Boston College Working Papers in Economics 558, Boston College Department of Economics.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    20. 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.
    21. 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.
    22. 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.
    23. Bensalma, Ahmed, 2018. "Two Distinct Seasonally Fractionally Differenced Periodic Processes," MPRA Paper 84969, University Library of Munich, Germany.
    24. 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.
    25. 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.
    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.

  174. 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. Stella Moisan & Rodrigo Herrera & Adam Clements, 2017. "A Dynamic Multiple Equation Approach for Forecasting PM2.5 Pollution in Santiago, Chile," NCER Working Paper Series 117, National Centre for Econometric Research.
    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 9780521770415, September.
    4. 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.
    5. 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.
    6. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
    7. 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.
    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. 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.
    10. 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).
    11. 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.
    12. 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.
    13. 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.

  175. 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.

  176. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.
    See citations under working paper version above.
  177. 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. 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.
    2. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
    3. 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.
    4. Dillon Alleyne, 2006. "Can Seasonal Unit Root Testing Improve the Forecasting Accuracy of Tourist Arrivals?," Tourism Economics, , vol. 12(1), pages 45-64, March.
    5. 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.
    6. 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.
    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. 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.
    9. Artur C. B. da Silva Lopes & Antonio Montanes, 2005. "The Behavior Of Hegy Tests For Quarterly Time Series With Seasonal Mean Shifts," Econometric Reviews, Taylor & Francis Journals, vol. 24(1), pages 83-108.
    10. 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.
    11. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    12. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    13. 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.
    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. 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).

  178. 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. Sørensen, Nils Karl, 2002. "Modelling and seasonal forecasting of monthly hotel nights in Denmark," ERSA conference papers ersa02p114, European Regional Science Association.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Tomás Barrio Castro & Andrii Bodnar & Andreu Sansó, 2017. "Numerical distribution functions for seasonal unit root tests with OLS and GLS detrending," Computational Statistics, Springer, vol. 32(4), pages 1533-1568, December.
    8. Otero, Jesus & Smith, Jeremy & Giulietti, Monica, 2008. "Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence," Economic Research Papers 269863, University of Warwick - Department of Economics.
    9. Pedro M G Martins, 2010. "Capital Inflows Hinder Competitiveness? The Real Exchange Rate in Ethiopia," Discussion Papers 10/07, University of Nottingham, CREDIT.
    10. Hassler, Uwe & Rodrigues, Paulo M. M., 2002. "Seasonal Unit Root Tests under Structural Breaks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 37696, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    11. Haldrup, Niels Prof. & Montanes, Antonio & Sansó, Andreu, 2000. "Measurement Errors and Outliers in Seasonal Unit Root Testing," University of California at San Diego, Economics Working Paper Series qt0gw7q9hk, Department of Economics, UC San Diego.
    12. 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.
    13. 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.
    14. 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.
    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. 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.
    17. Anna Serena Vergori, 2017. "Patterns of seasonality and tourism demand forecasting," Tourism Economics, , vol. 23(5), pages 1011-1027, August.
    18. Pedro M G Martins, 2010. "Fiscal Dynamics in Ethiopia: A Cointegrated VAR Model with Quarterly Data," Discussion Papers 10/05, University of Nottingham, CREDIT.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. Möbert, Jochen, 2007. "Crude oil price determinants," Darmstadt Discussion Papers in Economics 186, Darmstadt University of Technology, Department of Law and Economics.
    27. Tiwari, Aviral Kumar & Dutta, Subhendu & Dash, Aruna Kumar, 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), December.
    28. Diego Vásquez, 2003. "Crecimiento Económico y Concentración Original del Ingreso: Experiencias Internacionales desde 1820," Borradores de Economia 237, Banco de la Republica de Colombia.
    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. 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.
    32. 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.
    33. 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.
    34. 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.
    35. Anna Serena Vergori, 2012. "Forecasting Tourism Demand: The Role of Seasonality," Tourism Economics, , vol. 18(5), pages 915-930, October.
    36. Hamori, Shigeyuki, 2001. "Seasonality and stock returns: some evidence from Japan," Japan and the World Economy, Elsevier, vol. 13(4), pages 463-481, December.
    37. 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.
    38. 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.
    39. 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.
    40. Tiwari, Aviral, 2010. "Is trade deficit sustainable in India? An inquiry," MPRA Paper 24451, University Library of Munich, Germany.
    41. 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.
    42. Roche, M.J. & McQuinn, K., 2002. "Grain Price Volatility in a Small Open Economy," Economics Department Working Paper Series n1130202.pdf, Department of Economics, National University of Ireland - Maynooth.
    43. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    44. Maria Blangiewicz & Krystyna Strzala, 2008. "Notes on a Forecasting Procedure," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 8, pages 75-84.
    45. 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.
    46. 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.
    47. 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).
    48. 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.
    49. Luis A. Gil-Alana & Juncal Cunado & Fernando Perez de Gracia, 2008. "Tourism in the Canary Islands: forecasting using several seasonal time series models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 621-636.
    50. Pedro Martins, 2011. "Do large capital inflows hinder competitiveness? The Dutch disease in Ethiopia," Post-Print hal-00748067, HAL.
    51. 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.
    52. 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.
    53. 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(1), pages 1-16, June.
    54. 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.
    55. 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.
    56. Domenico Depalo, 2009. "A seasonal unit-root test with Stata," Stata Journal, StataCorp LP, vol. 9(3), pages 422-438, September.
    57. 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.
    58. 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.
    59. 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.
    60. 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.

  179. 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. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," EconomiX Working Papers 2014-46, University of Paris Nanterre, EconomiX.
    2. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," Working Papers hal-04141310, HAL.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

  180. 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. 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.
    4. Francis X. Diebold & Lutz Kilian, 1999. "Unit Root Tests are Useful for Selecting Forecasting Models," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-063, New York University, Leonard N. Stern School of Business-.
    5. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia.
    6. 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.
    7. Franco Bevilacqua & Adriaan van Zon, 2004. "Random walks and non-linear paths in macroeconomic time series: some evidence and implications," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 3, Edward Elgar Publishing.
    8. 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.

  181. 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.

    Cited by:

    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.

  182. 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. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    2. 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.
    3. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Papers 9510, Tilburg - Center for Economic Research.
    4. 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.
    5. Tomas del Barrio Castro & Denise R Osborn, 2005. "Cointegration for Periodically Integrated Processes," Economics Discussion Paper Series 0522, Economics, The University of Manchester.
    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. 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. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Clements, Michael & Smith, Jeremy, 1997. "Forecasting Seasonal Uk Consumption Components," Economic Research Papers 268761, University of Warwick - Department of Economics.
    14. 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.
    15. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    16. 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.
    17. 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.
    18. 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.
    19. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.
    20. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    21. Elizabeth Bucacos, 2008. "Real (effective) exchange rate in Uruguay: a periodic cointegration approach," Monetaria, CEMLA, vol. 0(2), pages 265-289, julio-sep.
    22. 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.
    23. Smith, Richard J. & Taylor, A.M. Robert & del Barrio Castro, Tomas, 2009. "Regression-Based Seasonal Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 25(2), pages 527-560, April.
    24. 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.
    25. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    26. Siem Jan Koopman & Marius Ooms & M. Angeles Carnero, 2005. "Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 05-091/4, Tinbergen Institute.
    27. 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.
    28. 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.
    29. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    30. 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.
    31. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    32. 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.
    33. Dean Fantazzini, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-27, November.
    34. Maekawa, Koichi, 1997. "Periodically integrated autoregression with a structural break," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 467-473.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Working Papers 1320, Department of Applied Economics II, Universidad de Valencia.
    40. 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.
    41. 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.
    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. 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.
    44. 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.
    45. 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.

  183. 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.
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  184. 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. 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. 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.
    3. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    4. 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.
    5. 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.
    6. Yoshinori Kawasaki, 1996. "A Model Selection Approach to detect Seasonal Unit Roots," Tinbergen Institute Discussion Papers 96-180/7, Tinbergen Institute.
    7. De Gooijer, Jan G. & Franses, Philip Hans, 1997. "Forecasting and seasonality," International Journal of Forecasting, Elsevier, vol. 13(3), pages 303-305, September.
    8. 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.
    9. Tucker McElroy & Anindya Roy, 2022. "A Review of Seasonal Adjustment Diagnostics," International Statistical Review, International Statistical Institute, vol. 90(2), pages 259-284, August.
    10. 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.
    11. Linsenmeier, Manuel, 2024. "Seasonal temperature variability and economic cycles," Journal of Macroeconomics, Elsevier, vol. 79(C).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Hecq, Alain, 1998. "Does seasonal adjustment induce common cycles?," Economics Letters, Elsevier, vol. 59(3), pages 289-297, June.
    21. 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.
    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. 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.
    24. 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.
    25. 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.
    26. Emanuela Marrocu, 2006. "An Investigation of the Effects of Data Transformation on Nonlinearity," Empirical Economics, Springer, vol. 31(4), pages 801-820, November.
    27. 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.
    28. 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.
    29. 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.
    30. 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.

  185. 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.

  186. 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. 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.
    3. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    4. Anna Serena Vergori, 2017. "Patterns of seasonality and tourism demand forecasting," Tourism Economics, , vol. 23(5), pages 1011-1027, August.
    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. 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.
    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. 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.
    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. 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.
    11. Lee, Hahn Shik & Siklos, Pierre L., 1997. "The role of seasonality in economic time series reinterpreting money-output causality in U.S. data," International Journal of Forecasting, Elsevier, vol. 13(3), pages 381-391, September.
    12. Lawrence J. Christiano & Richard M. Todd, 2000. "The Conventional Treatment of Seasonality in Business Cycle Analysis: Does it Create Distortions?," NBER Technical Working Papers 0266, National Bureau of Economic Research, Inc.
    13. Artur Da Silva Lopes, 2004. "Deterministic Seasonality In Dickey-Fuller Tests: Should We Care?," Royal Economic Society Annual Conference 2004 75, Royal Economic Society.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Nasir Hamid Rao & Syed Kalim Hyder Bukhari & Abdul Jalil, 2011. "Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited," Working Papers id:4290, eSocialSciences.
    19. 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.
    20. 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.
    21. 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.
    22. Leschinski, Christian & Sibbertsen, Philipp, 2019. "Model order selection in periodic long memory models," Econometrics and Statistics, Elsevier, vol. 9(C), pages 78-94.
    23. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  187. 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 & Kai Ming Lee, 0000. "Seasonality with Trend and Cycle Interactions in Unobserved Components Models," Tinbergen Institute Discussion Papers 08-028/4, Tinbergen Institute.
    2. Philip Stevens, 2004. "Skill Shortages and Firms' Employment Behaviour," National Institute of Economic and Social Research (NIESR) Discussion Papers 240, National Institute of Economic and Social Research.
    3. 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.
    4. 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.
    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. 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.

  188. 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.

  189. 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. 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.
    3. 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.
    4. 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.
    5. 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.

  190. 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. 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.
    2. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    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. 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.
    5. Lawrence J. Christiano & Richard M. Todd, 2000. "The Conventional Treatment of Seasonality in Business Cycle Analysis: Does it Create Distortions?," NBER Technical Working Papers 0266, National Bureau of Economic Research, Inc.
    6. 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.
    7. Bensalma, Ahmed, 2018. "Two Distinct Seasonally Fractionally Differenced Periodic Processes," MPRA Paper 84969, University Library of Munich, Germany.
    8. 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.
    9. 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.
    10. Hansen, Hermann-Josef, 1996. "The impact of interest rates on private consumption in Germany," Discussion Paper Series 1: Economic Studies 1996,03e, Deutsche Bundesbank.

  191. 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. 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.
    2. 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.
    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. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    5. 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.
    6. 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].
    7. 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.

  192. 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. Tomas del Barrio Castro & Denise R Osborn, 2005. "Cointegration for Periodically Integrated Processes," Economics Discussion Paper Series 0522, Economics, The University of Manchester.
    2. 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.
    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.

  193. 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. Tomas del Barrio Castro & Denise R Osborn, 2005. "Cointegration for Periodically Integrated Processes," Economics Discussion Paper Series 0522, Economics, The University of Manchester.
    2. 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.
    3. 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.
    4. del Barrio Castro, Tomás, 2022. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 112730, University Library of Munich, Germany, revised 2022.
    5. 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.
    6. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    7. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    8. 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.
    9. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    10. Younes Ben Zaied & Marie-Estelle Binet, 2015. "Modelling seasonality in residential water demand: the case of Tunisia," Post-Print halshs-01102007, HAL.
    11. Dr. Godwin Chukwudum Nwaobi, 2004. "Modelling Economic Fluctuations In Subsaharan Africa:A Vector Autoregressive Approach," Macroeconomics 0406008, University Library of Munich, Germany.
    12. 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.
    13. David R. Bell & Ronald C. Griffin, 2011. "Urban Water Demand with Periodic Error Correction," Land Economics, University of Wisconsin Press, vol. 87(3), pages 528-544.
    14. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    15. 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.
    16. 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.
    17. Lawrence J. Christiano & Richard M. Todd, 2000. "The Conventional Treatment of Seasonality in Business Cycle Analysis: Does it Create Distortions?," NBER Technical Working Papers 0266, National Bureau of Economic Research, Inc.
    18. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Working Papers 1320, Department of Applied Economics II, Universidad de Valencia.
    19. 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.
    20. 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.

  194. Franses, Philip Hans & Haldrup, Niels, 1994. "The Effects of Additive Outliers on Tests for Unit Roots and Cointegration," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 471-478, October.

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    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. Cati, Regina Celia & Garcia, Marcio G P & Perron, Pierre, 1999. "Unit Roots in the Presence of Abrupt Governmental Interventions with an Application to Brazilian Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(1), pages 27-56, Jan.-Feb..
    3. 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.
    4. WenShwo Fang & Stephen M. Miller & ChunShen Lee, 2007. "Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and GARCH Models," Working papers 2007-20, University of Connecticut, Department of Economics, revised Mar 2008.
    5. 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.
    6. Eduardo P. S. Fiuza & Fabiana F. M. Tito, 2015. "Time Series Econometrics in a Post-acquisition Antitrust Analysis: the Brazilian Iron ore Market," Discussion Papers 0182, Instituto de Pesquisa Econômica Aplicada - IPEA.
    7. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    8. Kufenko, Vadim & Khaustova, Ekaterina & Geloso, Vincent, 2022. "Escape underway: Malthusian pressures in late imperial Moscow," Explorations in Economic History, Elsevier, vol. 85(C).
    9. Chris Murray & Charles Nelson, 1998. "The Uncertain Trend in U.S. GDP," Discussion Papers in Economics at the University of Washington 0074, Department of Economics at the University of Washington.
    10. Saadet Kasman & Adnan Kasman & Duygu Ayhan, 2010. "Testing the Purchasing Power Parity Hypothesis for the New Member and Candidate Countries of the European Union: Evidence from Lagrange Multiplier Unit Root Tests with Structural Breaks," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(2), pages 53-65, March.
    11. Kai Carstensen, 2003. "The finite-sample performance of robust unit root tests," Statistical Papers, Springer, vol. 44(4), pages 469-482, October.
    12. Abadir, Karim M. & Lucas, Andre, 2000. "Quantiles for t-statistics based on M-estimators of unit roots," Economics Letters, Elsevier, vol. 67(2), pages 131-137, May.
    13. Olivier Darne & Jean-Francois Hoarau, 2007. "The purchasing power parity in Australia: evidence from unit root test with structural break," Applied Economics Letters, Taylor & Francis Journals, vol. 15(3), pages 203-206.
    14. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    15. Hafner, Christian & Preminger, Arie, 2015. "The effect of additive outliers on a fractional unit root test," LIDAM Discussion Papers ISBA 2015027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    17. Rendón, Juan F. & Cortés, Lina M. & Perote, Javier, 2024. "Basel III countercyclical bank capital buffer estimation and its relation to monetary policy," Journal of Economics and Business, Elsevier, vol. 130(C).
    18. Ng, S. & Perron, P., 1995. "Estimation and Inference in Nearly Unbalanced, Nearly Cointegrated Systems," Cahiers de recherche 9534, Universite de Montreal, Departement de sciences economiques.
    19. Haldrup, Niels Prof. & Montanes, Antonio & Sansó, Andreu, 2000. "Measurement Errors and Outliers in Seasonal Unit Root Testing," University of California at San Diego, Economics Working Paper Series qt0gw7q9hk, Department of Economics, UC San Diego.
    20. Nielsen, Morten Ørregaard, 2009. "A Powerful Test Of The Autoregressive Unit Root Hypothesis Based On A Tuning Parameter Free Statistic," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1515-1544, December.
    21. Maican, Florin G. & Sweeney, Richard J., 2013. "Real exchange rate adjustment in European transition countries," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 907-926.
    22. Jushan Bai; Josep Lluís Carrion-i-Silvestre, 2004. "Structural changes, common stochastic trends and unit roots in panel data," Econometric Society 2004 North American Summer Meetings 345, Econometric Society.
    23. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    24. Jesús Otero & Jeremy Smith, 2005. "The KPSS Test with Outliers," Computational Economics, Springer;Society for Computational Economics, vol. 26(3), pages 59-67, November.
    25. Fell, Harrison, 2008. "EU-ETS and Nordic Electricity: A CVAR Approach," RFF Working Paper Series dp-08-31, Resources for the Future.
    26. José Américo Pereira Antunes & Claudio Oliveira De Moraes & Gabriel Caldas Montes, 2016. "Bank Regulatory Capital, Risk-Taking Channel And Monetary Policy: Evidence From An Inflation Targeting Emerging Economy," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 042, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    27. Olivier Darné & Jean-François Hoarau, 2006. "Testing the purchasing power parity in China," EconomiX Working Papers 2006-18, University of Paris Nanterre, EconomiX.
    28. 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.
    29. Thiago Cacicedo Cidad & Gabriel Caldas Montes, 2016. "Does Central Bank’S Perception Regarding The State Of The Economy Affect Entrepreneurs’ Expectations? Are Entrepreneurs’ Expectations Important For Investment? Empirical Evidence From Brazil," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 035, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    30. Niels Haldrup & Antonio Montañés & Andreu Sansó, 2005. "Testing for Additive Outliers in Seasonally Integrated Time Series," DEA Working Papers 15, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    31. Olivier Darné & Claude Diebolt, 2006. "Chocs temporaires et permanents dans le PIB de la France, du Royaume-Uni et des États-Unis," Revue d'économie politique, Dalloz, vol. 116(1), pages 65-78.
    32. Hoek, Henk & Lucas, Andre & van Dijk, Herman K., 1995. "Classical and Bayesian aspects of robust unit root inference," Journal of Econometrics, Elsevier, vol. 69(1), pages 27-59, September.
    33. Lee, Tae-Hwy & Tse, Yiuman, 1996. "Cointegration tests with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 73(2), pages 401-410, August.
    34. Chen, Jie, 2006. "Re-evaluating the association between housing wealth and aggregate consumption: New evidence from Sweden," Journal of Housing Economics, Elsevier, vol. 15(4), pages 321-348, December.
    35. Niels Haldrup & Peter Møllgaard & Claus Kastberg Nielslen, 2005. "Sequential versus simultaneous market delineation: The relevant antitrust market for salmon," Economics Working Papers 2005-05, Department of Economics and Business Economics, Aarhus University.
    36. 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.
    37. Charles R. Nelson & Jeremy M. Piger & Eric Zivot, 2001. "Markov regime switching and unit root tests," Working Papers 2001-013, Federal Reserve Bank of St. Louis.
    38. Paul Castillo & Alberto Humala & Vicente Tuesta, 2007. "Monetary Policy, Regime Shifts, and Inflation Uncertainty in Peru (1949-2006)," Working Papers 2007-005, Banco Central de Reserva del Perú.
    39. Syed Abul Basher & Stefano Fachin, 2014. "Investigating long-run demand for broad money in the Gulf Arab countries," Middle East Development Journal, Taylor & Francis Journals, vol. 6(2), pages 199-214, July.
    40. 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.
    41. 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.
    42. Olivier Darné & Jean‐François Hoarau, 2007. "Further Evidence On Mean Reversion In The Australian Exchange Rate," Bulletin of Economic Research, Wiley Blackwell, vol. 59(4), pages 383-395, October.
    43. Niels Framroze Møller & Paul Sharp, 2008. "Malthus in Cointegration Space: A new look at living standards and population in pre-industrial England," Discussion Papers 08-16, University of Copenhagen. Department of Economics.
    44. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    45. Niels Haldrup & Andreu Sansó, 2006. "A Note on the Vogelsang Test for Additive Outliers," Economics Working Papers 2006-01, Department of Economics and Business Economics, Aarhus University.
    46. Hande Kucuk & Burc Tuger, 2004. "Relative Price Variability : The Case Of Turkey 1994-2002," Working Papers 0402, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    47. Morten Ø. Nielsen, 2008. "A Powerful Tuning Parameter Free Test Of The Autoregressive Unit Root Hypothesis," Working Paper 1175, Economics Department, Queen's University.
    48. Montes, Gabriel Caldas & Tavares, Debora Pereira & Guillén, Osmani Teixeira de Carvalho, 2013. "Canal de Transmissão da Política Monetária Por Meio dos Seguros Contratados Pelo Setor Bancário," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(3), September.
    49. 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.
    50. Carlomagno, Guillermo, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    51. Shin, Dong Wan & So, Beong Soo, 1999. "New tests for unit roots in autoregressive processes with possibly infinite variance errors," Statistics & Probability Letters, Elsevier, vol. 44(4), pages 387-397, October.
    52. Hirsch, Tristan & Rinke, Saskia, 2017. "Changes in Persistence in Outlier Contaminated Time Series," Hannover Economic Papers (HEP) dp-583, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    53. Gabriel Rodriguez, 2013. "A Comparative Note About Estimation of the Fractional Parameter under Additive Outliers," Documentos de Trabajo / Working Papers 2013-356, Departamento de Economía - Pontificia Universidad Católica del Perú.
    54. J. Isaac Miller, 2018. "Testing Cointegrating Relationships Using Irregular and Non-Contemporaneous Series with an Application to Paleoclimate Data," Working Papers 1809, Department of Economics, University of Missouri.
    55. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    56. Gabriel Rodriguez & Dionisio Ramirez, 2014. "A Note on the Size of the ADF Test with Additive Outliers and Fractional Errors. A Reappraisal about the (Non)Stationarity of the Latin-American Inflation Series," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 37(73), pages 113-132.
    57. Jungmittag Andre & Grupp Hariolf, 2006. "Wechselwirkungen zwischen Innovations- und Wachstumsprozessen in Deutschland 1951-1999 im Vergleich zu 1850-1913 / Dynamic Relationships Between Innovation Activities and Per Capita Income in Germany ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(2), pages 180-207, April.
    58. Adam E. Clements & A. Stan Hurn & Zili Li, 2017. "The Effect of Transmission Constraints on Electricity Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    59. Newbold, Paul & Leybourne, Stephen & Wohar, Mark E., 2001. "Trend-stationarity, difference-stationarity, or neither: further diagnostic tests with an application to U.S. Real GNP, 1875-1993," Journal of Economics and Business, Elsevier, vol. 53(1), pages 85-102.
    60. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    61. Gabriel Caldas Montes & Caroline Cabral Machado, 2013. "Credibility and the credit channel transmission of monetary policy theoretical model and econometric analysis for Brazil," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 40(4), pages 469-492, August.
    62. Darné, Olivier, 2009. "The uncertain unit root in real GNP: A re-examination," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 153-166, March.
    63. Charles Nelson & Jeremy Piger & Eric Zivot, 1999. "Unit Root Tests in the Presence of Markov Regime-Switching," Discussion Papers in Economics at the University of Washington 0040, Department of Economics at the University of Washington.
    64. Eduardo P. S. Fiuza & Fabiana F.M. Tito, 2007. "Time Series Econometrics in a Post-Acquisition Antitrust Analysis: The Brazilian Iron Ore Market," Discussion Papers 1306, Instituto de Pesquisa Econômica Aplicada - IPEA.
    65. Olivier Darné, 2004. "The effects of additive outliers on stationarity tests: a monte carlo study," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-8.
    66. Shin, Dong Wan & Sarkar, Sahadeb & Lee, Jong Hyup, 1996. "Unit root tests for time series with outliers," Statistics & Probability Letters, Elsevier, vol. 30(3), pages 189-197, October.
    67. Gabriel Caldas Montes & Julio Cesar Albuquerque Bastos, 2014. "Effects of reputation and credibility on monetary policy: theory and evidence for Brazil," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(3), pages 387-404, May.
    68. Olivier Darne & Laetitia Ripoll-Bresson, 2004. "Exchange rate regime classification and real performances: new empirical evidence," Money Macro and Finance (MMF) Research Group Conference 2003 21, Money Macro and Finance Research Group.
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    Cited by:

    1. 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.
    2. Tomas del Barrio Castro & Denise R Osborn, 2005. "Cointegration for Periodically Integrated Processes," Economics Discussion Paper Series 0522, Economics, The University of Manchester.
    3. 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.
    4. 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.
    5. Jiajie Kong & Robert Lund, 2023. "Seasonal count time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 93-124, January.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    12. 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.
    13. Franses, Philip Hans & Hylleberg, Svend & Lee, Hahn S., 1995. "Spurious deterministic seasonality," Economics Letters, Elsevier, vol. 48(3-4), pages 249-256, June.
    14. Smith, Richard J. & Taylor, A.M. Robert & del Barrio Castro, Tomas, 2009. "Regression-Based Seasonal Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 25(2), pages 527-560, April.
    15. 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.
    16. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    17. 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.
    18. 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.
    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. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    21. 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.
    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. 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.
    24. Justyna Wr'oblewska, 2020. "Bayesian analysis of seasonally cointegrated VAR model," Papers 2012.14820, arXiv.org, revised Apr 2021.
    25. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    26. 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.
    27. 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.
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    30. 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.
    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. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Working Papers 1320, Department of Applied Economics II, Universidad de Valencia.
    39. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    40. Mr. Francis Y Kumah, 2006. "The Role of Seasonality and Monetary Policy in Inflation Forecasting," IMF Working Papers 2006/175, International Monetary Fund.
    41. 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.
    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. 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.
    45. 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.
    46. 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.
    47. 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.
    48. Kunst, Robert M., 2009. "A Nonparametric Test for Seasonal Unit Roots," Economics Series 233, Institute for Advanced Studies.
    49. Bauer, Dietmar, 2019. "Periodic and seasonal (co-)integration in the state space framework," Economics Letters, Elsevier, vol. 174(C), pages 165-168.

  196. 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. 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.
    2. 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.
    3. 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.
    4. Clements, Michael & Smith, Jeremy, 1997. "Forecasting Seasonal Uk Consumption Components," Economic Research Papers 268761, University of Warwick - Department of Economics.
    5. 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.
    6. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    7. Breitung, Jorg & Franses, Philip Hans, 1997. "Impulse response functions for periodic integration," Economics Letters, Elsevier, vol. 55(1), pages 35-40, August.
    8. 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.
    9. T. Manouchehri & A. R. Nematollahi, 2019. "Periodic autoregressive models with closed skew-normal innovations," Computational Statistics, Springer, vol. 34(3), pages 1183-1213, September.
    10. Eiji Kurozumi, 2002. "Testing For Periodic Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 243-270.
    11. 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.
    12. Franses, Philip Hans & McAleer, Michael, 1997. "Testing periodically integrated autoregressive models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 457-465.
    13. 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.
    14. 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.
    15. Lawrence J. Christiano & Richard M. Todd, 2000. "The Conventional Treatment of Seasonality in Business Cycle Analysis: Does it Create Distortions?," NBER Technical Working Papers 0266, National Bureau of Economic Research, Inc.
    16. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Working Papers 1320, Department of Applied Economics II, Universidad de Valencia.
    17. 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.
    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. 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.
    20. Albertson, Kevin & Aylen, Jonathan, 2003. "Forecasting the behaviour of manufacturing inventory," International Journal of Forecasting, Elsevier, vol. 19(2), pages 299-311.
    21. 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.

  197. 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. Tomas del Barrio Castro & Denise R Osborn, 2005. "Cointegration for Periodically Integrated Processes," Economics Discussion Paper Series 0522, Economics, The University of Manchester.
    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.

  198. 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. 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.
    2. 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.
    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. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    5. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    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. 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.
    8. 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.
    9. 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.

  199. 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.

  200. 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.

  201. 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. 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.
    2. 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.
    3. Shintani, Mototsugu, 2001. "A simple cointegrating rank test without vector autoregression," Journal of Econometrics, Elsevier, vol. 105(2), pages 337-362, December.
    4. Kascha, Christian & Trenkler, Carsten, 2011. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1008-1017, February.
    5. 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.
    6. 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.
    7. 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.
    8. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.
    9. 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).
    10. L'Horty, Yannick & Rault, Christophe, 2003. "Why Is French Equilibrium Unemployment So High? An Estimation of the WS-PS Model," Journal of Applied Economics, Universidad del CEMA, vol. 6(1), pages 1-30, May.
    11. 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.
    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. 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.
    15. H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2023. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Econometric Reviews, Taylor & Francis Journals, vol. 42(9-10), pages 725-757, November.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Park, Moon-Soo & Jin, Yanhong H. & Bessler, David A., 2008. "The Impacts of Animal Disease Crises on the Korean Meat Market," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6365, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    23. 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.
    24. Jing Li & Junsoo Lee, 2010. "ADL tests for threshold cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 241-254, July.
    25. 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).
    26. 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.
    27. Rashid, Shahidur, 2002. "Dynamics of agricultural wage and rice price in Bangladesh," MTID discussion papers 44, International Food Policy Research Institute (IFPRI).
    28. Beine, Michel & Hecq, Alain, 1998. "Codependence and Convergence in the EC Economies," Journal of Policy Modeling, Elsevier, vol. 20(4), pages 403-426, August.
    29. 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.
    30. Judith A. Giles & Sadaf Mirza, 1999. "Some Pretesting Issues on Testing for Granger Noncausality," Econometrics Working Papers 9914, Department of Economics, University of Victoria.
    31. 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.
    32. 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.
    33. 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.
    34. Matthew Doyle & Barry Falk, 2008. "Testing Commitment Models of Monetary Policy: Evidence from OECD Economies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 409-425, March.
    35. Jose Manuel Gonzalez-Paramo, 1995. "Infraestructuras, productividad y bienestar," Investigaciones Economicas, Fundación SEPI, vol. 19(1), pages 155-168, January.
    36. 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.
    37. Holtedahl, Pernille & Joutz, Frederick L., 2004. "Residential electricity demand in Taiwan," Energy Economics, Elsevier, vol. 26(2), pages 201-224, March.
    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.

  202. 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.

  203. 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.

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

    Cited by:

    1. Ollech, Daniel & Webel, Karsten, 2020. "A random forest-based approach to identifying the most informative seasonality tests," Discussion Papers 55/2020, Deutsche Bundesbank.
    2. 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.
    3. Ghysels, E., 1993. "A Time Series Model with Periodic Stochastic Regime Switching," Cahiers de recherche 9314, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. Webel, Karsten, 2016. "A data-driven selection of an appropriate seasonal adjustment approach," Discussion Papers 07/2016, Deutsche Bundesbank.

  205. 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, 2006. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 419-438, May.
    2. 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.
    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. 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.
    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. 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.

  206. 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.
  207. 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 & Zakoïan, Jean-Michel, 2022. "Testing the existence of moments for GARCH processes," Journal of Econometrics, Elsevier, vol. 227(1), pages 47-64.

  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," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università 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, September.

    Cited by:

    1. 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. Philip Hans Franses, 2021. "Estimating persistence for irregularly spaced historical data," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(6), pages 2177-2187, December.
    3. 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.
    4. 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.
    5. Philip Hans Franses, 2018. "Prediction Intervals For Expert-Adjusted Forecasts," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 308-320, December.
    6. 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.
    7. 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.
    8. 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).
    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. 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.
    11. 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.

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

    Cited by:

    1. Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    3. Philip Hans Franses & Bert Bruijn, 2017. "Benchmarking Judgmentally Adjusted Forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 3-11, January.
    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. 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.
    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. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
    12. 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.
    13. 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.
    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, September.

    Cited by:

    1. 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.
    2. 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.
    3. Zewei Lin & Dungang Liu, 2022. "Model diagnostics of discrete data regression: a unifying framework using functional residuals," Papers 2207.04299, arXiv.org.
    4. 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.
    5. 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.
    6. 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.
    7. David A. Schweidel & George Knox, 2013. "Incorporating Direct Marketing Activity into Latent Attrition Models," Marketing Science, INFORMS, vol. 32(3), pages 471-487, May.
    8. 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.
    9. Fernández-Durán, J.J., 2016. "Defining generational cohorts for marketing in Mexico," Journal of Business Research, Elsevier, vol. 69(2), pages 435-444.
    10. 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.
    11. Mohamed Abdallah Ali & Mazhar Mughal & Charles Kodjo Mawusi, 2021. "Does Khat Consumption Affect Work Performance ? A Micro-Perspective from Djibouti," Working Papers hal-03375659, HAL.
    12. Vicari, Donatella & Alfó, Marco, 2014. "Model based clustering of customer choice data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 3-13.
    13. 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.
    14. Adel Ben Youssef & Mounir Dahmani & Nessrine Omrani, 2013. "Information technologies, students'e-skills and diversity of learning process," Post-Print halshs-00937145, HAL.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Yabing Jiang & Hong Guo, 2015. "Design of Consumer Review Systems and Product Pricing," Information Systems Research, INFORMS, vol. 26(4), pages 714-730, December.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. Zhao, Li & Tian, Peng & Xiangyong Li, 2012. "Dynamic pricing in the presence of consumer inertia," Omega, Elsevier, vol. 40(2), pages 137-148, April.
    39. 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.
    40. Defrancesco, Edi, 2002. "The Beginning Of Organic Fish Farming In Italy," Working Papers 14367, University of Minnesota, Center for International Food and Agricultural Policy.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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).
    47. Fok, D. & Paap, R., 2003. "Modeling category-level purchase timing with brand-level marketing variables," Econometric Institute Research Papers 1715, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. Eoghan O'Neill, 2022. "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression," Papers 2211.07506, arXiv.org, revised Feb 2024.
    53. 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.
    54. 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.
    55. 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.
    56. 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.
    57. 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.
    58. 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.
    59. 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.
    60. 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.

  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. 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. Franses, Philip Hans, 2013. "Data revisions and periodic properties of macroeconomic data," Economics Letters, Elsevier, vol. 120(2), pages 139-141.
    4. Aknouche, Abdelhakim & Guerbyenne, Hafida, 2009. "Periodic stationarity of random coefficient periodic autoregressions," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 990-996, April.
    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. 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).
    7. Jiajie Kong & Robert Lund, 2023. "Seasonal count time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 93-124, January.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Ursu, Eugen & Duchesne, Pierre, 2009. "On multiplicative seasonal modelling for vector time series," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 2045-2052, October.
    13. 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.
    14. Nicholas J. Cox, 2009. "Stata tip 76: Separating seasonal time series," Stata Journal, StataCorp LP, vol. 9(2), pages 321-326, June.
    15. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    16. Panagiotelis, Anastasios & Smith, Michael, 2010. "Bayesian skew selection for multivariate models," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1824-1839, July.
    17. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    18. Dillon Alleyne, 2006. "Can Seasonal Unit Root Testing Improve the Forecasting Accuracy of Tourist Arrivals?," Tourism Economics, , vol. 12(1), pages 45-64, March.
    19. 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.
    20. Aknouche, Abdelhakim & Rabehi, Nadia, 2024. "Inspecting a seasonal ARIMA model with a random period," MPRA Paper 120758, University Library of Munich, Germany.
    21. 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.
    22. Franses, Ph.H.B.F., 2006. "Forecasting 1 to h steps ahead using partial least squares," Econometric Institute Research Papers EI 2006-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. 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.
    24. Niels Haldrup & Antonio Montañés & Andreu Sansó, 2005. "Testing for Additive Outliers in Seasonally Integrated Time Series," DEA Working Papers 15, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    25. T. Manouchehri & A. R. Nematollahi, 2019. "Periodic autoregressive models with closed skew-normal innovations," Computational Statistics, Springer, vol. 34(3), pages 1183-1213, September.
    26. 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.
    27. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    28. 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.
    29. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    30. 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.
    31. 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.
    32. 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.
    33. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
    34. Abdelhakim Aknouche & Eid Al-Eid, 2012. "Asymptotic inference of unstable periodic ARCH processes," Statistical Inference for Stochastic Processes, Springer, vol. 15(1), pages 61-79, April.
    35. 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.
    36. 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.
    37. Eugen Ursu & Pierre Duchesne, 2009. "On modelling and diagnostic checking of vector periodic autoregressive time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 70-96, January.
    38. Tucker McElroy & Anindya Roy, 2022. "A Review of Seasonal Adjustment Diagnostics," International Statistical Review, International Statistical Institute, vol. 90(2), pages 259-284, August.
    39. Amaal Elsayed Mubarak & Ehab Mohamed Almetwally, 2024. "Modelling and Forecasting of Covid-19 Using Periodical ARIMA Models," Annals of Data Science, Springer, vol. 11(4), pages 1483-1502, August.
    40. Hindrayanto, Irma & Koopman, Siem Jan & Ooms, Marius, 2010. "Exact maximum likelihood estimation for non-stationary periodic time series models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2641-2654, November.
    41. Abdelhakim Aknouche & Abdelouahab Bibi, 2009. "Quasi‐maximum likelihood estimation of periodic GARCH and periodic ARMA‐GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 19-46, January.
    42. 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.
    43. Dimitrios Thomakos & Hossein Hassani & Kerry Patterson, 2013. "Optimal Linear Filtering, Smoothing and Trend Extraction for the m-th Differences of a Unit Root Process: A Singular Spectrum Analysis Approach," Economics Discussion Papers em-dp2013-04, Department of Economics, University of Reading.
    44. Q. Shao, 2008. "Robust Estimation For Periodic Autoregressive Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 251-263, March.
    45. 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.
    46. Roy, Roch & Saidi, Abdessamad, 2008. "Aggregation and systematic sampling of periodic ARMA processes," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4287-4304, May.
    47. Domenico Cucina & Manuel Rizzo & Eugen Ursu, 2018. "Identification of multiregime periodic autotregressive models by genetic algorithms," Post-Print hal-03187870, HAL.
    48. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    49. Vaz, Lucélia Viviane & Filho, Getulio Borges da Silveira, 2017. "Functional Autoregressive Models: An Application to Brazilian Hourly Electricity Load," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(2), November.
    50. Francesco Battaglia & Domenico Cucina & Manuel Rizzo, 2020. "Detection and estimation of additive outliers in seasonal time series," Computational Statistics, Springer, vol. 35(3), pages 1393-1409, September.
    51. 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.
    52. Dean Fantazzini, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-27, November.
    53. 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.
    54. Boshnakov, Georgi N. & Lambert-Lacroix, Sophie, 2012. "A periodic Levinson-Durbin algorithm for entropy maximization," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 15-24, January.
    55. 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.
    56. Siem Jan Koopman & Marius Ooms, 2004. "Forecasting Daily Time Series using Periodic Unobserved Components Time Series Models," Tinbergen Institute Discussion Papers 04-135/4, Tinbergen Institute.
    57. Aknouche, Abdelhakim & Guerbyenne, Hafida, 2009. "On some probabilistic properties of double periodic AR models," Statistics & Probability Letters, Elsevier, vol. 79(3), pages 407-413, February.
    58. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Working Papers 1320, Department of Applied Economics II, Universidad de Valencia.
    59. PEREAU Jean-Christophe & URSU Eugen, 2015. "Application of periodic autoregressive process to the modeling of the Garonne river flows," Cahiers du GREThA (2007-2019) 2015-14, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    60. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, September.
    61. 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.
    62. 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.
    63. 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.
    64. 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.
    65. Geoffrey Coke & Min Tsao, 2010. "Random effects mixture models for clustering electrical load series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 451-464, November.
    66. Tashpulatov, Sherzod N., 2013. "Estimating the volatility of electricity prices: The case of the England and Wales wholesale electricity market," Energy Policy, Elsevier, vol. 60(C), pages 81-90.
    67. Georgi N. Boshnakov & Bisher M. Iqelan, 2009. "Generation Of Time Series Models With Given Spectral Properties," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 349-368, May.
    68. Lenart, Łukasz, 2013. "Non-parametric frequency identification and estimation in mean function for almost periodically correlated time series," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 252-269.
    69. 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.
    70. 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.
    71. Aknouche, Abdelhakim, 2024. "Periodically homogeneous Markov chains: The discrete state space case," MPRA Paper 122287, University Library of Munich, Germany.
    72. 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. 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.
    74. 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.
    75. Fadiga, Mohamadou L. & Misra, Sukant K., 2005. "Asymmetry, Risk, and Correlation Dynamics in the U.S. Fiber Market," 2005 Annual meeting, July 24-27, Providence, RI 19459, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    76. Lucélia Vaz & Rodrigo Raad, 2021. "Functional data analysis for brazilian term structure of interest rate," Textos para Discussão Cedeplar-UFMG 638, Cedeplar, Universidade Federal de Minas Gerais.
    77. 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.
    78. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, December.
    79. 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.
    80. Bruno Bosco & Lucia Parisio & Matteo Pelagatti, 2007. "Deregulated Wholesale Electricity Prices in Italy: An Empirical Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 13(4), pages 415-432, November.
    81. Amaral, Luiz Felipe & Souza, Reinaldo Castro & Stevenson, Maxwell, 2008. "A smooth transition periodic autoregressive (STPAR) model for short-term load forecasting," International Journal of Forecasting, Elsevier, vol. 24(4), pages 603-615.
    82. 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.

  5. Heij, Christiaan & de Boer, Paul & Franses, Philip Hans & Kloek, Teun & van Dijk, Herman K., 2004. "Econometric Methods with Applications in Business and Economics," OUP Catalogue, Oxford University Press, number 9780199268016.

    Cited by:

    1. 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.
    2. Aleksandra Szymańska & Stijn Van Puyvelde & Marc Jegers, 2015. "Capital structure of social purpose companies -- a panel data analysis," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 5(4), pages 234-254, October.
    3. Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
    4. Blum, Bianca, 2018. "Ausgestaltung einer Steuerpolitik zur Förderung von LED-Beleuchtung," The Constitutional Economics Network Working Papers 01-2018, University of Freiburg, Department of Economic Policy and Constitutional Economic Theory.
    5. Bjarne Jensen & Paul Boer & Jan Daal & Peter Jensen, 2011. "Global restrictions on the parameters of the CDES indirect utility function," Journal of Economics, Springer, vol. 102(3), pages 217-235, April.
    6. Singh, Sanjay Kumar, 2006. "Future mobility in India: Implications for energy demand and CO2 emission," Transport Policy, Elsevier, vol. 13(5), pages 398-412, September.
    7. Afia Malik, 2010. "Oil Prices and Economic Activity in Pakistan," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 11(2), pages 223-244, September.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.
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    14. 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.
    15. Ghassan, Hassan B. & Taher, Farid B., 2013. "Financial Stability of Islamic and Conventional Banks in Saudi Arabia: Evidence using Pooled and Panel Models," MPRA Paper 54472, University Library of Munich, Germany, revised Dec 2013.
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    18. Niklas Elert, 2014. "What determines entry? Evidence from Sweden," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 55-92, August.
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    22. 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.
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    27. 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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    79. 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).
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    81. Isaksen, Elisabeth T. & Narbel, Patrick A., 2017. "A carbon footprint proportional to expenditure - A case for Norway?," Ecological Economics, Elsevier, vol. 131(C), pages 152-165.
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    83. Sana Abusin & Brian W. Mandikiana & Noor Al Emadi & Fahad Al-Boinin, 2022. "Socioeconomic Drivers of Fish Consumption in Qatar," Sustainability, MDPI, vol. 14(17), pages 1-12, September.
    84. Wickes, Ron, 2021. "Trade deficits and trade conflict: The United States and Japan," Japan and the World Economy, Elsevier, vol. 60(C).
    85. Odolinski, Kristofer & Nilsson, Jan-Eric, 2016. "Estimating the marginal maintenance cost of rail infrastructure usage in Sweden; does more data make a difference?," Working papers in Transport Economics 2016:27, CTS - Centre for Transport Studies Stockholm (KTH and VTI), revised 13 May 2017.
    86. Martin Campbell-Kelly & Daniel D. Garcia-Swartz & Dhiren Patki, 2012. "Information Technology and Establishment Size in America: Rybczynski Redivivus☆," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 19(2), pages 337-357, July.
    87. Tirfi, Abera Gayesa & Oyekale, Abayomi Samuel, 2021. "Maize Output Supply Response to Climatic and Other Input Variables in Ethiopia," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society (AESS), vol. 11(04), January.
    88. 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.
    89. Elias Sanidas & Kankesu Jayanthakumaran, 2008. "Trade liberalization and lagged reactions of trade flows, productivity and internal demand: an application to the Australian PMV industry," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 13(1), pages 26-49.
    90. Nenubari Ikue John & Emeka Nkoro & Jeremiah Anietie, 2021. "Time-Gap effects of crude oil prices on the foreign exchange rates: Evidence from Nigeria," Bussecon Review of Social Sciences (2687-2285), Bussecon International Academy, vol. 3(3), pages 31-44, July.
    91. Hollander, Hilke & Prokop, Jörg, 2015. "Stock price effects of asset securitization: The case of liquidity facility providers," The Quarterly Review of Economics and Finance, Elsevier, vol. 57(C), pages 147-160.
    92. Adam, P. & Rianse, U. & Harafah, Ĺ. M. & Cahyono, E. & Rafiy, M., 2016. "A Model of the Dynamics of the Effect of World Crude Oil Price and World Rice Price on Indonesia’s Inflation Rate," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 8(1), pages 1-10, March.
    93. Harwin de Vries & Albert P M Wagelmans & Epco Hasker & Crispin Lumbala & Pascal Lutumba & Sake J de Vlas & Joris van de Klundert, 2016. "Forecasting Human African Trypanosomiasis Prevalences from Population Screening Data Using Continuous Time Models," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-23, September.
    94. Knapp, S., 2020. "Quantification and analysis of risk exposure in the maritime industry," Econometric Institute Research Papers EI 2020-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    95. 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.
    96. 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.
    97. 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.
    98. 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.
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  6. Franses,Philip Hans, 2002. "A Concise Introduction to Econometrics," Cambridge Books, Cambridge University Press, number 9780521520904, September.

    Cited by:

    1. Simplice A. Asongu & Jacinta C. Nwachukwu, 2017. "Quality of Growth Empirics: Comparative Gaps, Benchmarking and Policy Syndromes," Research Africa Network Working Papers 17/034, Research Africa Network (RAN).
    2. 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).
    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. 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.
    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, September.

    Cited by:

    1. 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.
    2. 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.
    3. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    4. 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.
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