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Andrew C. Harvey

Not to be confused with: Andrew Sydney Harvey

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. Andrew Harvey & Jared Bernstein, 2003. "Measurement and Testing of Inequality from Time Series of Deciles with an Application to U.S. Wages," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 141-152, February.

    Mentioned in:

    1. Forecasting and Tomorrow’s Jobs Report
      by Jared Bernstein in On the Economy on 2012-07-06 00:56:08

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.

    Mentioned in:

    1. Convergence in the trends and cycles of Euro-zone income (Journal of Applied Econometrics 2005) in ReplicationWiki ()
  2. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.

    Mentioned in:

    1. Testing against smooth stochastic trends (Journal of Applied Econometrics 2001) in ReplicationWiki ()
  3. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.

    Mentioned in:

    1. Detrending, stylized facts and the business cycle (Journal of Applied Econometrics 1993) in ReplicationWiki ()
  4. Author Profile
    1. Andrew Harvey in Wikipedia (German)

Working papers

  1. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.

  2. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.

  3. Andrew C. Harvey, 2020. "Time series models for epidemics: leading indicators, control groups and policy assessment," National Institute of Economic and Social Research (NIESR) Discussion Papers 517, National Institute of Economic and Social Research.

    Cited by:

    1. Monika Baloda, 2023. "The Tech Decoupling," Papers 2304.00510, arXiv.org.

  4. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," 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. 29(3), pages 859-874, September.
    2. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    3. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.

  5. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    2. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).

  6. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    2. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.

  7. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.

  8. Harvey, A. & Thiele, S., 2017. "Co-integration and control: assessing the impact of events using time series data," Cambridge Working Papers in Economics 1731, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Kim, Hyejin & Lee, Jungmin, 2019. "Can employment subsidies save jobs? Evidence from a shipbuilding city in South Korea," Labour Economics, Elsevier, vol. 61(C).
    2. Takamitsu Kurita & Bent Nielsen, 2019. "Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms," Econometrics, MDPI, vol. 7(4), pages 1-35, October.
    3. Peter Dreuw, 2023. "Structural time series models and synthetic controls—assessing the impact of the euro adoption," Empirical Economics, Springer, vol. 64(2), pages 681-725, February.
    4. Henry Aray & David Vera, 2023. "A Tale of Oil Production Collapse," ThE Papers 23/10, Department of Economic Theory and Economic History of the University of Granada..
    5. Anderson, Heather M. & Gao, Jiti & Turnip, Guido & Vahid, Farshid & Wei, Wei, 2023. "Estimating the effect of an EU-ETS type scheme in Australia using a synthetic treatment approach," Energy Economics, Elsevier, vol. 125(C).
    6. Duc A. Nguyen & Steven Brakman & Harry Garretsen & Tristan Kohl, 2024. "Mean Reversion of the German City System After the WWII Bombing of Cities: What Is the Mean?," CESifo Working Paper Series 11423, CESifo.
    7. Farid, Moatazbellah, 2020. "The Effect of Brexit on UK Productivity: Synthetic Control Analysis," MPRA Paper 103165, University Library of Munich, Germany.

  9. Andrew Harvey & Rutger-Jan Lange, 2015. "Volatility Modeling with a Generalized t-distribution," Cambridge Working Papers in Economics 1517, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    2. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    3. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    4. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org.
    5. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    6. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    7. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    8. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    9. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    10. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    11. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    12. Victor Korolev, 2023. "Analytic and Asymptotic Properties of the Generalized Student and Generalized Lomax Distributions," Mathematics, MDPI, vol. 11(13), pages 1-27, June.
    13. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    14. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    15. Ruijie Guan & Xu Zhao & Weihu Cheng & Yaohua Rong, 2021. "A New Generalized t Distribution Based on a Distribution Construction Method," Mathematics, MDPI, vol. 9(19), pages 1-36, September.
    16. Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2021. "Analytic moments for GJR-GARCH (1, 1) processes," International Journal of Forecasting, Elsevier, vol. 37(1), pages 105-124.
    17. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    18. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    19. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    20. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    21. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    22. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    23. Ayala, Astrid & Blazsek, Szabolcs, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    24. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    25. Karol Kielak & Robert Ślepaczuk, 2020. "Value-at-risk — the comparison of state-of-the-art models on various assets," Working Papers 2020-28, Faculty of Economic Sciences, University of Warsaw.
    26. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    27. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    28. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    29. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    30. Kamil Makie{l}a & B{l}a.zej Mazur, 2020. "Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging," Papers 2003.07150, arXiv.org, revised Oct 2020.
    31. Higbee, Joshua D. & McDonald, James B., 2024. "A comparison of the GB2 and skewed generalized log-t distributions with an application in finance," Journal of Econometrics, Elsevier, vol. 240(2).
    32. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    33. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    34. Van Tran, Quang & Kukal, Jaromir, 2024. "Renyi entropy based design of heavy tailed distribution for return of financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    35. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.
    36. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    37. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.
    38. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    39. Dennis Umlandt, 2020. "Likelihood-based Dynamic Asset Pricing: Learning Time-varying Risk Premia from Cross-Sectional Models," Working Paper Series 2020-06, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    40. Fabrizio Leisen & Luca Rossini & Cristiano Villa, 2020. "Loss-based approach to two-piece location-scale distributions with applications to dependent data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 309-333, June.
    41. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  10. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    2. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    3. Liu, Dehong & Gu, Hongmei & Lung, Peter, 2016. "The equity mispricing: Evidence from China's stock market," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 211-223.

  11. Andrew Harvey & Stephen Thiele, 2014. "Testing against Changing Correlation," Cambridge Working Papers in Economics 1439, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2021. "Modeling and forecasting macroeconomic downside risk," Temi di discussione (Economic working papers) 1324, Bank of Italy, Economic Research and International Relations Area.
    2. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    4. Sakurai, Yuji & Kurosaki, Tetsuo, 2023. "Have cryptocurrencies become an inflation hedge after the reopening of the U.S. economy?," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Andrew Harvey & Dario Palumbo, 2023. "Regime switching models for circular and linear time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 374-392, July.
    6. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    7. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    8. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    9. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    10. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.
    11. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    12. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    13. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    14. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.
    15. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.

  12. Michele Caivano & Andrew Harvey, 2014. "Time series models with an EGB2 conditional distribution," Temi di discussione (Economic working papers) 947, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    2. Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2021. "Modeling and forecasting macroeconomic downside risk," Temi di discussione (Economic working papers) 1324, Bank of Italy, Economic Research and International Relations Area.
    3. Blasques, F. & van Brummelen, J. & Gorgi, P. & Koopman, S.J., 2024. "A robust Beveridge–Nelson decomposition using a score-driven approach with an application," Economics Letters, Elsevier, vol. 236(C).
    4. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    5. Saissi Hassani, Samir & Dionne, Georges, 2021. "The New International Regulation of Market Risk: Roles of VaR and CVaR in Model Validation," Working Papers 21-1, HEC Montreal, Canada Research Chair in Risk Management.
    6. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    7. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    8. Jingyu Ji & Hang Lin, 2022. "Evaluating Regional Carbon Inequality and Its Dependence with Carbon Efficiency: Implications for Carbon Neutrality," Energies, MDPI, vol. 15(19), pages 1-35, September.
    9. M. Caivano & A. Harvey, 2013. "Time series models with an EGB2 conditional distribution," Cambridge Working Papers in Economics 1325, Faculty of Economics, University of Cambridge.
    10. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    11. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    12. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    13. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    14. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    15. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    16. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    17. M. Caivano & A. Harvey, 2013. "Two EGARCH models and one fat tail," Cambridge Working Papers in Economics 1326, Faculty of Economics, University of Cambridge.
    18. Michele Caivano & Andrew Harvey & Alessandra Luati, 2016. "Robust time series models with trend and seasonal components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 99-120, March.
    19. Higbee, Joshua D. & McDonald, James B., 2024. "A comparison of the GB2 and skewed generalized log-t distributions with an application in finance," Journal of Econometrics, Elsevier, vol. 240(2).
    20. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    21. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.

  13. Michele Caivano & Andrew Harvey, 2014. "Two EGARCH models and one fat tail," Temi di discussione (Economic working papers) 954, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    2. Taneli M�kinen, 2014. "Informed trading and stock market efficiency," Temi di discussione (Economic working papers) 992, Bank of Italy, Economic Research and International Relations Area.
    3. Giuseppe Ferrero & Marcello Miccoli & Sergio Santoro, 2014. "Informational Effects of Monetary Policy," Temi di discussione (Economic working papers) 982, Bank of Italy, Economic Research and International Relations Area.

  14. Harvey, A. & Sucarrat, G., 2012. "EGARCH models with fat tails, skewness and leverage," Cambridge Working Papers in Economics 1236, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
    2. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
    3. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    4. Szabolcs Blazsek & Vicente Mendoza, 2016. "QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1119-1129, March.
    5. Hasanov, Akram Shavkatovich & Burkhanov, Aktam Usmanovich & Usmonov, Bunyod & Khajimuratov, Nizomjon Shukurullaevich & Khurramova, Madina Mansur qizi, 2024. "The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks," Energy, Elsevier, vol. 293(C).
    6. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    7. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    8. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    9. Fernanda Maria Müller & Fábio M Bayer, 2017. "Improved two-component tests in Beta-Skew-t-EGARCH models," Economics Bulletin, AccessEcon, vol. 37(4), pages 2364-2373.
    10. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    11. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    12. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    13. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    14. Irving Arturo De Lira Salvatierra & Andrew J. Patton, 2013. "Dynamic Copula Models and High Frequency Data," Working Papers 13-28, Duke University, Department of Economics.
    15. Fatih Kazova & Ayça Büyükyılmaz Ercan, 2021. "Comparative Analysis of the Volatility Structure of Cryptocurrencies," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(35), pages 33-57, December.
    16. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    17. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    18. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    19. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
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    50. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
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    55. Sonia Benito Muela & Carmen López-Martín & Mª Ángeles Navarro, 2017. "The Role of the Skewed Distributions in the Framework of Extreme Value Theory (EVT)," International Business Research, Canadian Center of Science and Education, vol. 10(11), pages 88-102, November.
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    60. Yacouba Boubacar Maïnassara & Othman Kadmiri & Bruno Saussereau, 2022. "Portmanteau test for the asymmetric power GARCH model when the power is unknown," Statistical Papers, Springer, vol. 63(3), pages 755-793, June.
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    Cited by:

    1. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    2. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    3. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    4. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    5. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Sampi Bravo,James Robert Ezequiel & Jooste,Charl & Vostroknutova,Ekaterina, 2021. "Identification Properties for Estimating the Impact of Regulation on Markups and Productivity," Policy Research Working Paper Series 9523, The World Bank.
    7. Saverio Ranciati & Alberto Roverato & Alessandra Luati, 2021. "Fused graphical lasso for brain networks with symmetries," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1299-1322, November.
    8. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    9. Blasques, F. & van Brummelen, J. & Gorgi, P. & Koopman, S.J., 2024. "A robust Beveridge–Nelson decomposition using a score-driven approach with an application," Economics Letters, Elsevier, vol. 236(C).
    10. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    11. Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations Of Market Forecasts, And Sentiment," Discussion Papers 17-10, University of Copenhagen. Department of Economics.
    12. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    13. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    14. Caballero, Diego & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2019. "Risk endogeneity at the lender/investor-of-last-resort," Working Paper Series 2225, European Central Bank.
    15. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    16. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    17. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    18. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    19. Lucas, André & Zhang, Xin, 2015. "Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting," Working Paper Series 309, Sveriges Riksbank (Central Bank of Sweden).
    20. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    21. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    22. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    23. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
    24. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    25. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    26. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    27. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    28. M. Caivano & A. Harvey, 2013. "Time series models with an EGB2 conditional distribution," Cambridge Working Papers in Economics 1325, Faculty of Economics, University of Cambridge.
    29. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    30. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    31. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    32. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    33. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
    34. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    35. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    36. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    37. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    38. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    39. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    40. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    41. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    42. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    43. Francisco Blasques & Siem Jan Koopman & Andre Lucas & Julia Schaumburg, 2014. "Spillover Dynamics for Systemic Risk Measurement using Spatial Financial Time Series Models," Tinbergen Institute Discussion Papers 14-107/III, Tinbergen Institute.
    44. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    45. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    46. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    47. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    48. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    49. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    50. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    51. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    52. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    53. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.
    54. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    55. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    56. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
    57. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    58. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    59. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    60. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    61. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    62. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    63. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    64. Beaumont, Adrian N., 2014. "Data transforms with exponential smoothing methods of forecasting," International Journal of Forecasting, Elsevier, vol. 30(4), pages 918-927.
    65. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    66. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    67. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    68. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    69. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    70. Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
    71. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    72. Michele Caivano & Andrew Harvey & Alessandra Luati, 2016. "Robust time series models with trend and seasonal components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 99-120, March.
    73. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    74. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    75. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    76. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.

  16. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    2. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    3. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    4. Parley Ruogu Yang, 2021. "Forecasting high-frequency financial time series: an adaptive learning approach with the order book data," Papers 2103.00264, arXiv.org.
    5. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.
    6. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    7. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.

  17. Harvey, A., 2010. "Exponential Conditional Volatility Models," Cambridge Working Papers in Economics 1040, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    2. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    3. Igor Kheifets, 2014. "Specification Tests for Nonlinear Dynamic Models," Cowles Foundation Discussion Papers 1937, Cowles Foundation for Research in Economics, Yale University, revised Oct 2014.
    4. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    5. Wintenberger, Olivier & Cai, Sixiang, 2011. "Parametric inference and forecasting in continuously invertible volatility models," MPRA Paper 31767, University Library of Munich, Germany.
    6. Bernd Schwaab, 2012. "Conditional probabilities and contagion measures for euro area sovereign default risk," Research Bulletin, European Central Bank, vol. 17, pages 6-11.
    7. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    8. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.

  18. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    2. Henry Penikas, 2016. "Copula-Based Univariate Time Series Structural Shift Identification Test," Papers 1609.05056, arXiv.org.
    3. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.

  19. Harvey, A., 2008. "Modeling the Phillips curve with unobserved components," Cambridge Working Papers in Economics 0805, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Mallick, Debdulal, 2019. "Policy regimes and the shape of the Phillips curve in Australia," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1077-1094.
    2. Mengheng Li & Ivan Mendieta-Munoz, 2019. "The multivariate simultaneous unobserved components model and identification via heteroskedasticity," Working Paper Series 2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    3. Kavtaradze, Lasha, 2014. "Inflation Dynamics in Georgia," MPRA Paper 59966, University Library of Munich, Germany.
    4. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
    5. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    6. Kajuth, Florian, 2010. "NAIRU estimates for Germany: New evidence on the inflation-unemployment trade-off," Discussion Paper Series 1: Economic Studies 2010,19, Deutsche Bundesbank.
    7. Winkelried, Diego, 2023. "Simple interpolations of inflation expectations," Economics Letters, Elsevier, vol. 229(C).
    8. Sumru Altug & Cem Cakmakli, 2014. "Inflation Targeting and Inflation Expectations: Evidence for Brazil and Turkey," Koç University-TUSIAD Economic Research Forum Working Papers 1413, Koc University-TUSIAD Economic Research Forum.
    9. Macchiarelli, Corrado, 2011. "Bond market co-movements, expected inflation and the equilibrium real exchange rate," Working Paper Series 1405, European Central Bank.
    10. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    11. Kajuth, Florian, 2012. "Identifying the Phillips curve through shifts in volatility," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 975-991.
    12. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    13. De la Serve, M-E. & Lemoine, M., 2011. "Measuring the NAIRU: a complementary approach," Working papers 342, Banque de France.
    14. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    15. Mallick, Debdulal, 2014. "A Spectral Representation of the Phillips Curve in Australia," MPRA Paper 59794, University Library of Munich, Germany.
    16. Mengheng Li & Irma Hindrayanto, 2018. "Looking for the stars: Estimating the natural rate of interest," Working Paper Series 51, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    17. Byron J. Idrovo-Aguirre & Javier E. Contreras-Reyes, 2019. "Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015," Empirical Economics, Springer, vol. 57(5), pages 1829-1852, November.
    18. Basistha, Arabinda & Kurov, Alexander, 2010. "Estimating earnings trend using unobserved components framework," Economics Letters, Elsevier, vol. 107(1), pages 55-57, April.
    19. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    20. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    21. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    22. Antonio, Paradiso & Kumar, Saten & Rao, B Bhaskara, 2011. "A New Keynesian IS Curve for Australia: Is it Forward Looking or Backward Looking?," MPRA Paper 35296, University Library of Munich, Germany.
    23. Pym Manopimoke, 2012. "Hong Kong Inflation Dynamics: Trend and Cycle Relationships with the U.S. and China," Working Papers 232012, Hong Kong Institute for Monetary Research.
    24. James McNeil & Gregor W. Smith, 2023. "The All‐Gap Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 269-282, April.
    25. Lena Vogel, 2008. "The Relationship between the Hybrid New Keynesian Phillips Curve and the NAIRU over Time," Macroeconomics and Finance Series 200803, University of Hamburg, Department of Socioeconomics.
    26. Paradiso, Antonio & Rao, B. Bhaskara, 2011. "Flattening of the Phillips Curve and the Role of Oil Price: An Unobserved Components Model for the USA and Australia," MPRA Paper 29606, University Library of Munich, Germany.
    27. Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.
    28. Mohammad Naim Azimi, 2016. "Drawing on Phillips curve: does the inverse relation between inflation and unemployment persist in transitional economies," International Journal of Economics and Accounting, Inderscience Enterprises Ltd, vol. 7(2), pages 89-100.
    29. Hindrayanto, Irma & Samarina, Anna & Stanga, Irina M., 2019. "Is the Phillips curve still alive? Evidence from the euro area," Economics Letters, Elsevier, vol. 174(C), pages 149-152.
    30. Luca Agnello & Vítor Castro & Ricardo M. Sousa, 2023. "Interest rate gaps in an uncertain global context: why “too” low (high) for “so” long?," Empirical Economics, Springer, vol. 64(2), pages 539-565, February.

  20. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Benos, Nikos & Stavrakoudis, Athanassios, 2020. "Okun's Law: Copula-based Evidence from G7 Countries," MPRA Paper 103318, University Library of Munich, Germany.
    2. Thanaset Chevapatrakul & Kai-Hong Tee, 2014. "The Effects of News Events on Market Contagion: Evidence from the 2007-2009 Financial Crisis," Discussion Papers 2014/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    3. Yangguang Zhu & Feng Yang & Wuyi Ye, 2018. "Financial contagion behavior analysis based on complex network approach," Annals of Operations Research, Springer, vol. 268(1), pages 93-111, September.
    4. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    5. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    6. Dimitrios Panagiotou & Athanassios Stavrakoudis, 2023. "Price dependence among the major EU extra virgin olive oil markets: a time scale analysis," Review of Agricultural, Food and Environmental Studies, Springer, vol. 104(1), pages 1-26, March.
    7. Mensi, Walid & Selmi, Refk & Al-Yahyaee, Khamis Hamed, 2020. "Switching dependence and systemic risk between crude oil and U.S. Islamic and conventional equity markets: A new evidence," Resources Policy, Elsevier, vol. 69(C).
    8. Renee Fry-McKibbin & Cody Yu-Ling Hsiao & Vance L. Martin, 2017. "Joint tests of contagion with applications to financial crises," CAMA Working Papers 2017-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    10. Li, Fuchun & Zhu, Hui, 2014. "Testing for financial contagion based on a nonparametric measure of the cross-market correlation," Review of Financial Economics, Elsevier, vol. 23(3), pages 141-147.
    11. Panagiotou, Dimitrios & Stavrakoudis, Athanassios, 2017. "Vertical price relationships between different cuts and quality grades in the U.S. beef marketing channel: a wholesale-retail analysis," MPRA Paper 75989, University Library of Munich, Germany.
    12. Fousekis, Panos & Grigoriadis, Vasilis, 2017. "Price co-movement and the crack spread in the US futures markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 57-71.
    13. Krämer, Walter & van Kampen, Maarten, 2011. "A simple nonparametric test for structural change in joint tail probabilities," Economics Letters, Elsevier, vol. 110(3), pages 245-247, March.
    14. Dungey, Mardi & Flavin, Thomas J. & Lagoa-Varela, Dolores, 2020. "Are banking shocks contagious? Evidence from the eurozone," Journal of Banking & Finance, Elsevier, vol. 112(C).
    15. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    16. Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.
    17. Chollete, Loran & Ning, Cathy, 2009. "The Dependence Structure of Macroeconomic Variables in the US," UiS Working Papers in Economics and Finance 2009/31, University of Stavanger.
    18. Mardi Dungey & Eric Renault, 2018. "Identifying contagion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 227-250, March.
    19. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    20. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    21. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    22. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    23. Dungey, Mardi & Gajurel, Dinesh, 2013. "Equity Market Contagion during the Global Financial Crisis: Evidence from the World’s Eight Largest Economies," Working Papers 17213, University of Tasmania, Tasmanian School of Business and Economics, revised 16 Oct 2013.
    24. Renée Fry-McKibbin & Cody Yu-Ling Hsiao, 2015. "Extremal dependence tests for contagion," CAMA Working Papers 2015-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    25. Atskanov, Isuf, 2015. "Dynamic optimization of an investment portfolio on European stock markets using pair copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 40(4), pages 84-105.
    26. Hee Soo Lee & Tae Yoon Kim, 2022. "A new analytical approach for identifying market contagion," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-35, December.
    27. Wenying Yao & Mardi Dungey & Vitali Alexeev, 2020. "Modelling Financial Contagion Using High Frequency Data," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 314-330, September.
    28. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    29. Fabio Busetti, 2012. "On detecting end-of-sample instabilities," Temi di discussione (Economic working papers) 881, Bank of Italy, Economic Research and International Relations Area.
    30. Chevapatrakul, Thanaset & Tee, Kai-Hong, 2014. "The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis," Research in International Business and Finance, Elsevier, vol. 32(C), pages 83-105.
    31. Selmi, Refk & Hammoudeh, Shawkat & Kasmaoui, Kamal & Sousa, Ricardo M. & Errami, Youssef, 2022. "The dual shocks of the COVID-19 and the oil price collapse: A spark or a setback for the circular economy?," Energy Economics, Elsevier, vol. 109(C).
    32. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2017. "The changing international network of sovereign debt and financial institutions," Working Papers 2017-04, University of Tasmania, Tasmanian School of Business and Economics.
    33. Shenqiu Zhang & Ivan Paya & David Peel, 2009. "Linkages between Shanghai and Hong Kong stock indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(23), pages 1847-1857.
    34. Stavrakoudis, Athanassios & Panagiotou, Dimitrios, 2016. "Price dependence and asymmetric responses between coffee varieties," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 17(2), June.
    35. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.
    36. Mardi Dungey & Jet Holloway & Abdullah Yalaman & Wenying Yao, 2022. "Characterizing financial crises using high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 22(4), pages 743-760, April.
    37. Wied, Dominik & Dehling, Herold & van Kampen, Maarten & Vogel, Daniel, 2014. "A fluctuation test for constant Spearman’s rho with nuisance-free limit distribution," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 723-736.
    38. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    39. Tim Kutzker & Florian Stark & Dominik Wied, 2021. "Testing for relevant dependence change in financial data: a CUSUM copula approach," Empirical Economics, Springer, vol. 60(4), pages 1875-1894, April.
    40. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    41. Renée Fry-McKibbin & Vance Martin & Chrismin Tang, 2013. "Financial Contagion and Asset Pricing," CAMA Working Papers 2013-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    42. Rezitis, Anthony N. & Rokopanos, Andreas & Tsionas, Mike G., 2021. "Investigating dynamic price co-movements in the international milk market using copulas: The role of trade agreements," Economic Modelling, Elsevier, vol. 95(C), pages 215-227.
    43. Selmi, Refk & Wohar, Mark & Deisting, Florent & Kasmaoui, Kamal, 2023. "Dynamic inflation hedging performance and downside risk: A comparison between Islamic and conventional stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 56-67.
    44. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    45. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    46. Okyoung Na & Jiyeon Lee & Sangyeol Lee, 2013. "Change point detection in SCOMDY models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(3), pages 215-238, July.
    47. Bucher, Axel & Jaschke, Stefan & Wied, Dominik, 2013. "Nonparametric tests for constant tail dependence with an application to energy and finance," LIDAM Discussion Papers ISBA 2013033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  21. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    2. Thanaset Chevapatrakul & Kai-Hong Tee, 2014. "The Effects of News Events on Market Contagion: Evidence from the 2007-2009 Financial Crisis," Discussion Papers 2014/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    3. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    4. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.
    5. Chevapatrakul, Thanaset & Tee, Kai-Hong, 2014. "The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis," Research in International Business and Finance, Elsevier, vol. 32(C), pages 83-105.

  22. Fabio Busetti & Andrew Harvey, 2007. "Testing for trend," Temi di discussione (Economic working papers) 614, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Reitz, Stefan & Ruelke, Jan C. & Taylor, Mark P., 2010. "On the nonlinear influence of Reserve Bank of Australia interventions on exchange rates," Discussion Paper Series 1: Economic Studies 2010,08, Deutsche Bundesbank.
    2. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    3. Cavaliere, Giuseppe & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2011. "Testing For Unit Roots In The Presence Of A Possible Break In Trend And Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 27(5), pages 957-991, October.
    4. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Testing for Unit Roots and the Impact of Quadratic Trends, with an Application to Relative Primary Commodity Prices," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 514-547, October.
    5. Busetti, Fabio & Forni, Lorenzo & Harvey, Andrew & Venditti, Fabrizio, 2006. "Inflation convergence and divergence within the European Monetary Union," Working Paper Series 574, European Central Bank.
    6. Gadea Rivas, María Dolores, 2017. "Trends in distributional characteristics : Existence of global warming," UC3M Working papers. Economics 24121, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    8. Gomez Zaldivar, M. & Ventosa-Santaularia, D., 2009. "Bilateral Relationship between Consumption and GDP in Mexico and the USA: A Comment," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    9. James H. Stock & Mark W. Watson, 1996. "Asymptotically Median Unbiased Estimation of Coefficient Variance in a Time Varying Parameter Model," NBER Technical Working Papers 0201, National Bureau of Economic Research, Inc.
    10. 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.
    11. Giuseppe Cavaliere & A. M. Robert Taylor, 2006. "Testing for a change in persistence in the presence of non-stationary volatility," Discussion Papers 06/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    12. Chevillon, Guillaume, 2007. "Inference in the Presence of Stochastic and Deterministic Trends," ESSEC Working Papers DR 07021, ESSEC Research Center, ESSEC Business School.
    13. Peter C.B. Phillips & Tassos Magdalinos, 2008. "Unit Root and Cointegrating Limit Theory When Initialization Is in the Infinite Past," Cowles Foundation Discussion Papers 1655, Cowles Foundation for Research in Economics, Yale University.
    14. Jushan Bai & Serena Ng, 2001. "A New Look at Panel Testing of Stationarity and the PPP Hypothesis," Economics Working Paper Archive 467, The Johns Hopkins University,Department of Economics.
    15. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2007. "Unit root testing in practice: dealing with uncertainty over the trend and initial condition," Discussion Papers 07/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    16. Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
    17. 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.
    18. Joakim Westerlund & David L. Edgerton, 2007. "New Improved Tests for Cointegration with Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(2), pages 188-224, March.
    19. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    20. María Dolores Gadea Rivas & Jesús Gonzalo, 2022. "A tale of three cities: climate heterogeneity," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 475-511, May.
    21. James Morley & Tara M. Sinclair, 2005. "Testing for Stationarity and Cointegration in an Unobserved Components Framework," Computing in Economics and Finance 2005 451, Society for Computational Economics.
    22. Riccardo Corradini, 2005. "An Empirical Analysis of Permanent Income Hypothesis Applied to Italy using State Space Models with non zero correlation between trend and cycle," Econometrics 0509009, University Library of Munich, Germany.
    23. Sauro Mocetti, 2012. "Educational choices and the selection process: before and after compulsory schooling," Education Economics, Taylor & Francis Journals, vol. 20(2), pages 189-209, February.
    24. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    25. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Discussion Papers 08/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    26. Josep Carrion-i-Silvestre & Andreu Sansó, 2007. "The KPSS test with two structural breaks," Spanish Economic Review, Springer;Spanish Economic Association, vol. 9(2), pages 105-127, June.
    27. 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.
    28. Josep Lluís Carrion-i-Silvestre & Dukpa Kim & Pierre Perron, 2007. "GLS-based unit root tests with multiple structural breaks both under the null and the alternative hypotheses," Boston University - Department of Economics - Working Papers Series wp2008-019, Boston University - Department of Economics.
    29. 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.
    30. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.
    31. Chevillon, Guillaume, 2012. "Local-Explosive Approximations to Null Distributions of the Johansen Cointegration Test, with an Application to Cyclical Concordance in the Euro Area," ESSEC Working Papers WP1210, ESSEC Research Center, ESSEC Business School.
    32. Josep Lluis Carrion Silvestre & Tomas del Barrio Castro & Enrique Lopez Bazo, 2003. "Breaking the panels. An application to the GDP per capita," Working Papers in Economics 97, Universitat de Barcelona. Espai de Recerca en Economia.
    33. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2007. "Testing for a unit root when uncertain about the trend [Revised to become 07/03 above]," Discussion Papers 06/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    34. María Presno & Anna López, 2003. "Testing for stationarity in series with a shift in the mean. A fredholm approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 195-213, June.

  23. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Chan, Ngai Hang & Sit, Tony, 2016. "Artifactual unit root behavior of Value at risk (VaR)," Statistics & Probability Letters, Elsevier, vol. 116(C), pages 88-93.
    2. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    3. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    4. Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020. "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers) 1288, Bank of Italy, Economic Research and International Relations Area.
    5. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    6. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    7. Zhang, Feipeng & Li, Qunhua, 2017. "A continuous threshold expectile model," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 49-66.
    8. Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
    9. Luciano Stefanini & Maria Letizia Guerra, 2016. "On Possibilistic Representations of Fuzzy Intervals," Working Papers 1602, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2016.
    10. Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    11. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    12. Yuta Kurose & Yasuhiro Omori, 2012. "Bayesian Analysis of Time-Varying Quantiles Using a Smoothing Spline," CIRJE F-Series CIRJE-F-845, CIRJE, Faculty of Economics, University of Tokyo.
    13. Zhang, Feipeng & Xu, Yixiong & Fan, Caiyun, 2023. "Nonparametric inference of expectile-based value-at-risk for financial time series with application to risk assessment," International Review of Financial Analysis, Elsevier, vol. 90(C).
    14. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    15. Daouia, Abdelaati & Paindaveine, Davy, 2019. "Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression," TSE Working Papers 19-1022, Toulouse School of Economics (TSE), revised Feb 2023.
    16. Zhiping Chen & Qianhui Hu & Ruiyue Lin, 2016. "Performance ratio-based coherent risk measure and its application," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 681-693, May.
    17. Huang, Xiaolin & Shi, Lei & Suykens, Johan A.K., 2014. "Asymmetric least squares support vector machine classifiers," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 395-405.
    18. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    19. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    20. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
    21. Jakobsons Edgars, 2016. "Scenario aggregation method for portfolio expectile optimization," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 51-65, September.
    22. C. Adam & I. Gijbels, 2022. "Local polynomial expectile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 341-378, April.
    23. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    24. Chollete, Loran & Ning, Cathy, 2009. "The Dependence Structure of Macroeconomic Variables in the US," UiS Working Papers in Economics and Finance 2009/31, University of Stavanger.
    25. Bellini, Fabio & Klar, Bernhard & Müller, Alfred & Rosazza Gianin, Emanuela, 2014. "Generalized quantiles as risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 41-48.
    26. Abdelaati Daouia & Stéphane Girard & Gilles Stupfler, 2018. "Estimation of tail risk based on extreme expectiles," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(2), pages 263-292, March.
    27. Caperoz, Marcelo & Marçal, Emerson Fernandes & Mattos, Enlinson, 2016. "A time series analysis of household income inequality in Brazil 1977-2013," Textos para discussão 434, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    28. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    29. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    30. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    31. Luciano Stefanini, 2015. "Quantile and expectile smoothing by F-transform," Working Papers 1512, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2015.
    32. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.
    33. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    34. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    35. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    36. Zhijie Xiao & Roger Koenker, 2009. "Conditional Quantile Estimation for GARCH Models," Boston College Working Papers in Economics 725, Boston College Department of Economics.
    37. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    38. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    39. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    40. Chollete, Loran & de la Pena , Victor & Lu, Ching-Chih, 2009. "International Diversification: An Extreme Value Approach," UiS Working Papers in Economics and Finance 2009/26, University of Stavanger.
    41. Feng, Xiang-Nan & Wang, Yifan & Lu, Bin & Song, Xin-Yuan, 2017. "Bayesian regularized quantile structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 234-248.
    42. Federico Gatta & Fabrizio Lillo & Piero Mazzarisi, 2024. "CAESar: Conditional Autoregressive Expected Shortfall," Papers 2407.06619, arXiv.org.
    43. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    44. Shuzhen Yang, 2021. "Compensatory model for quantile estimation and application to VaR," Papers 2112.07278, arXiv.org.
    45. Bingzhen Geng & Yang Liu & Yimiao Zhao, 2024. "Value-at-Risk- and Expectile-based Systemic Risk Measures and Second-order Asymptotics: With Applications to Diversification," Papers 2404.18029, arXiv.org.
    46. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    47. Zongwu Cai & Ying Fang & Dingshi Tian, 2024. "CAViaR Model Selection Via Adaptive Lasso," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202403, University of Kansas, Department of Economics, revised Jan 2024.
    48. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    49. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
    50. Zongwu Cai & Ying Fang & Dingshi Tian, 2018. "Assessing Tail Risk Using Expectile Regressions with Partially Varying Coefficients," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201804, University of Kansas, Department of Economics, revised Oct 2018.
    51. Marcus Alexander & Matthew Harding & Carlos Lamarche, 2011. "Quantifying the impact of economic crises on infant mortality in advanced economies," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3313-3323.
    52. Voudouris, Vlasios & Matsumoto, Ken'ichi & Sedgwick, John & Rigby, Robert & Stasinopoulos, Dimitrios & Jefferson, Michael, 2014. "Exploring the production of natural gas through the lenses of the ACEGES model," Energy Policy, Elsevier, vol. 64(C), pages 124-133.
    53. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    54. Burdejova, Petra & Härdle, Wolfgang Karl & Kokoszka, Piotr & Xiong, Q., 2015. "Change point and trend analyses of annual expectile curves of tropical storms," SFB 649 Discussion Papers 2015-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  24. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
    2. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    3. Clive G. Bowsher & Roland Meeks, 2008. "The dynamics of economics functions: modelling and forecasting the yield curve," Working Papers 0804, Federal Reserve Bank of Dallas.
    4. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    5. Daniel Mariño-Ustacara & Luis Fernando Melo-Velandia, 2016. "Relación entre los valores en riesgo de los principales mercados financieros colombianos: un enfoque a través de modelos multivariados de regresión cuantílica," Borradores de Economia 975, Banco de la Republica de Colombia.
    6. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    7. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.
    8. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    9. Caperoz, Marcelo & Marçal, Emerson Fernandes & Mattos, Enlinson, 2016. "A time series analysis of household income inequality in Brazil 1977-2013," Textos para discussão 434, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    10. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    11. Nieto, María Rosa, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    13. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    14. Shuzhen Yang, 2021. "Compensatory model for quantile estimation and application to VaR," Papers 2112.07278, arXiv.org.

  25. Busetti, Fabio & Forni, Lorenzo & Harvey, Andrew & Venditti, Fabrizio, 2006. "Inflation convergence and divergence within the European Monetary Union," Working Paper Series 574, European Central Bank.

    Cited by:

    1. Jan Kubíček, 2006. "Úrokové diferenciály a zadlužení v eurozóně [Interest rate differentials and the debt in the euro-zone]," Politická ekonomie, Prague University of Economics and Business, vol. 2006(6), pages 816-833.
    2. Litsios, Ioannis & Pilbeam, Keith, 2017. "An empirical analysis of the nexus between investment, fiscal balances and current account balances in Greece, Portugal and Spain," Economic Modelling, Elsevier, vol. 63(C), pages 143-152.
    3. Dino Martellato, 2006. "Inflation and Growth in the Euro Zone," Working Papers 2006_52, Department of Economics, University of Venice "Ca' Foscari".
    4. P. Siklos & M. Bohl, 2006. "Asset Prices as Indicators of Euro Area Monetary Policy: An Empirical Assessment of Their Role in a Taylor Rule," Working Papers eg0053, Wilfrid Laurier University, Department of Economics, revised 2006.
    5. Garcia-Hiernaux, Alfredo & Guerrero, David E., 2021. "Price convergence: Representation and testing," Economic Modelling, Elsevier, vol. 104(C).
    6. Lopez, Claude & Papell, David, 2010. "Testing for Group-Wise Convergence with an Application to Euro Area Inflation," MPRA Paper 20585, University Library of Munich, Germany.
    7. Ulrich Fritsche & Vladimir Kuzin, 2007. "Unit Labor Cost Growth Differentials in the Euro Area, Germany, and the US: Lessons from PANIC and Cluster Analysis," Discussion Papers of DIW Berlin 667, DIW Berlin, German Institute for Economic Research.
    8. Sule Akkoyunlu & Boriss Siliverstovs, 2010. "Does the Law of One Price Hold in a High-Inflation Environment?," KOF Working papers 10-248, KOF Swiss Economic Institute, ETH Zurich.
    9. Dino Martellato, 2006. "Growth and Inflation Disparities in Corridor V," Working Papers 2006_19, Department of Economics, University of Venice "Ca' Foscari".
    10. Giray GOZGOR, 2013. "Unemployment Persistence and Inflation Convergence: Evidence from Regions of Turkey," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 13(1), pages 55-64.
    11. Bofinger, Peter & Mayer, Eric, 2004. "Monetary and Fiscal policy Interaction in the Euro Area with Different Assumptions on the Phillips Curve," CEPR Discussion Papers 4790, C.E.P.R. Discussion Papers.
    12. Joseph P. Byrne & Norbert Fiess, 2007. "Euro Area Inflation: Aggregation Bias and Convergence," Working Papers 2007_41, Business School - Economics, University of Glasgow.
    13. Giorgio Canarella & Stephen Miller & Stephen Pollard, 2011. "The Global Financial Crisis and Stochastic Convergence in the Euro Area," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 17(3), pages 315-333, August.
    14. Ulrich Fritsche & Vladimir Kuzin, 2011. "Analysing convergence in Europe using the non-linear single factor model," Empirical Economics, Springer, vol. 41(2), pages 343-369, October.
    15. Aycan HEPSAG, 2017. "Inflation convergence among the next eleven economies: Evidence from asymmetric nonlinear unit root test," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(613), W), pages 43-52, Winter.
    16. Sule Akkoyunlu & Boriss Siliverstovs, 2014. "Does the law of one price hold in a high-inflation environment? A tale of two cities in Turkey," Applied Economics, Taylor & Francis Journals, vol. 46(26), pages 3236-3245, September.
    17. Agnès Bénassy-Quéré, 2006. "Short-Term Fiscal Spillovers in a Monetary Union," Working Papers 2006-13, CEPII research center.
    18. Christian Dreger, 2008. "Does the Nominal Exchange Rate Regime Affect the Real Interest Parity Condition?," Working Paper / FINESS 1.1c, DIW Berlin, German Institute for Economic Research.
    19. Fabio Busetti & Pietro Cova & Antonio Maria Conti & Filippo Scoccianti & Libero Monteforte & Giordano Zevi & Valentina Aprigliano & Andrea Gerali & Alberto Locarno & Alessandro Notarpietro & Massimili, 2014. "The effects of the crisis on production potential and household spending in Italy," Workshop and Conferences 18, Bank of Italy, Economic Research and International Relations Area.
    20. Nektarios A. Michail, 2020. "Convergence of consumption patterns in the European Union," Empirical Economics, Springer, vol. 58(3), pages 979-994, March.
    21. Giulio Palomba & Emma Sarno & Alberto Zazzaro, 2009. "Testing similarities of short-run inflation dynamics among EU-25 countries after the Euro," Empirical Economics, Springer, vol. 37(2), pages 231-270, October.
    22. Garcia-Hiernaux, Alfredo & Gonzalez-Perez, Maria T. & Guerrero, David E., 2023. "Eurozone prices: A tale of convergence and divergence," Economic Modelling, Elsevier, vol. 126(C).
    23. Sebastian Dullien & Ulrich Fritsche, 2008. "Does the dispersion of unit labor cost dynamics in the EMU imply long-run divergence?," International Economics and Economic Policy, Springer, vol. 5(3), pages 269-295, November.
    24. Dovern, Jonas & Gern, Klaus-Jürgen & Jannsen, Nils & Van Roye, Björn & Scheide, Joachim & Boysen-Hogrefe, Jens & Meier, Carsten-Patrick, 2010. "Weltkonjunktur im Frühjahr 2010," Kiel Discussion Papers 476/477, Kiel Institute for the World Economy (IfW Kiel).
    25. Sondermann, David, 2012. "Productivity in the euro area: any evidence of convergence?," Working Paper Series 1431, European Central Bank.
    26. Daniel Dias, 2006. "Measuring the Importance of the Uniform Nonsynchronization Hypothesis," Working Papers w200603, Banco de Portugal, Economics and Research Department.
    27. SILVESTRINI, Andrea, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," LIDAM Reprints CORE 2220, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. Fabio C. Bagliano & Claudio Morana, 2010. "The effects of US economic and financial crises on euro area convergence," Working papers 15, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    29. König, Jörg & Ohr, Renate, 2012. "Messung ökonomischer Integration in der Europäischen Union: Entwicklung eines EU-Integrationsindexes," University of Göttingen Working Papers in Economics 135, University of Goettingen, Department of Economics.
    30. Bagnai, Alberto & Granville, Brigitte & Mongeau Ospina, Christian A., 2017. "Withdrawal of Italy from the euro area: Stochastic simulations of a structural macroeconometric model," Economic Modelling, Elsevier, vol. 64(C), pages 524-538.
    31. Giannellis, Nikolaos, 2013. "Asymmetric behavior of inflation differentials in the euro area: Evidence from a threshold unit root test," Research in Economics, Elsevier, vol. 67(2), pages 133-144.
    32. Moons, Cindy & Hellinckx, Kevin, 2019. "Did monetary policy fuel the housing bubble? An application to Ireland," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 294-315.
    33. Guglielmo Maria Caporale & Alexandros Kontonikas, 2006. "The Euro And Inflation Uncertainty In The European Monetary Union," Economics and Finance Discussion Papers 06-01, Economics and Finance Section, School of Social Sciences, Brunel University.
    34. Thushyanthan Baskaran, 2009. "Did the Maastricht treaty matter for macroeconomic performance? A difference‐in‐difference investigation," Kyklos, Wiley Blackwell, vol. 62(3), pages 331-358, August.
    35. Angelos Liontakis & Dimitris Kremmydas, 2013. "Food Inflation in EU: Distribution Analysis and Spatial Effects," Working Papers 2013-3, Agricultural University of Athens, Department Of Agricultural Economics.
    36. Alberto Bagnai, 2016. "Italy’s decline and the balance-of-payments constraint: a multicountry analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 30(1), pages 1-26, January.
    37. Arestis, Philip & Chortareas, Georgios & Magkonis, Georgios & Moschos, Demetrios, 2014. "Inflation targeting and inflation convergence: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 285-295.
    38. Alejandro C. García-Cintado & Diego Romero-Ávila & Carlos Usabiaga, 2016. "The economic integration of Spain: a change in the inflation pattern," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 25(1), pages 1-41, December.
    39. Brož, Václav & Kočenda, Evžen, 2018. "Dynamics and factors of inflation convergence in the European union," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 93-111.
    40. Alberto Bagnai, 2010. "CEEC vs. PIGS: a comparative panel assessment of financial sustainability and twin deficits," Working Papers LuissLab 1088, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    41. Busetti, Fabio & Harvey, Andrew, 2008. "Testing For Trend," Econometric Theory, Cambridge University Press, vol. 24(1), pages 72-87, February.
    42. Helmut Herwartz & Florian Siedenburg, 2013. "To converge or not converge: unit labor cost inflation in the Euro area," Empirical Economics, Springer, vol. 44(2), pages 455-467, April.
    43. Claude Lopez, 2008. "Euro-zone Inflation Rates: Stationary or Regime-wise Stationary Processes," University of Cincinnati, Economics Working Papers Series 2008-02, University of Cincinnati, Department of Economics, revised 2008.
    44. Václav Žďárek, 2011. "Empirická analýza průběhu cenové konvergence ČR a nových členských zemí EU k eurozóně [An Empirical Analysis of Price Convergence of the Czech Republic and the New EU Member States towards the Euro," Politická ekonomie, Prague University of Economics and Business, vol. 2011(4), pages 454-474.
    45. Juan Carlos Cuestas & Carlyn Ramlogan-Dobson, 2013. "Convergence of Inflationary Shocks: Evidence from the Caribbean," The World Economy, Wiley Blackwell, vol. 36(9), pages 1229-1243, September.
    46. Alberto Bagnai, 2013. "Unhappy families are all alike: Minskyan cycles, Kaldorian growth, and the Eurozone peripheral crises," a/ Working Papers Series 1301, Italian Association for the Study of Economic Asymmetries, Rome (Italy).
    47. Constantina Kottaridi & Diego Mendez-Carbajo & Dimitrios Thomakos, 2007. "Inflation Dynamics and the Cross-Sectional Distribution of Prices in the E.U. Periphery," Working Papers 0004, University of Peloponnese, Department of Economics.
    48. Andrea Vaona, 2006. "Merging the Purchasing Power Parity and the Phillips Curve Literatures: Regional Evidence from Italy," Working Papers 33/2006, University of Verona, Department of Economics.
    49. Eder, Andreas & Koller, Wolfgang & Mahlberg, Bernhard, 2019. "Price Competitiveness in the European Monetary Union: A Decomposition of Inflation Differentials based on the Leontief Input-Output Price Model for the Period 2000 to 2014," MPRA Paper 95158, University Library of Munich, Germany.
    50. Alfredo García Hiernaux & David Esteban Guerrero Burbano, 2015. "Price-Level Convergence in the Eurozone," Documentos de Trabajo del ICAE 2015-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    51. Karanasos, M. & Koutroumpis, P. & Karavias, Y. & Kartsaklas, A. & Arakelian, V., 2016. "Inflation convergence in the EMU," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 241-253.
    52. Pelinescu, Elena & Caraiani, Petre, 2006. "Does the Inflation Targeting Have a Positive Role upon the Convergence of the Inflation Rate?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 3(3), pages 39-50, September.
    53. Alberto Bagnai & Brigitte Granville & Christian Alexander Mongeau Ospina, 2017. "Withdrawal of Italy from the Eurozone: stochastic simulations of a structural macroeconometric model," a/ Working Papers Series 1702, Italian Association for the Study of Economic Asymmetries, Rome (Italy).
    54. Iulia Siedschlag, 2008. "Macroeconomic Differentials and Adjustment in the Euro Area," SUERF Studies, SUERF - The European Money and Finance Forum, number 2008/3 edited by Morten Balling, May.
    55. Adrian Petre, 2016. "The Analysis of the Nominal Convergence in the New Member States of the European Union," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(61), pages 245-254, September.
    56. Dridi, Jemma & Nguyen, Anh D. M., 2017. "Inflation Convergence In East African Countries," MPRA Paper 80393, University Library of Munich, Germany.
    57. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
    58. 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.
    59. Angelos Liontakis & Christos T. Papadas, 2010. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," Working Papers 2010-6, Agricultural University of Athens, Department Of Agricultural Economics.
    60. Bohl, Martin & Mayes, David G. & Siklos, Pierre L., 2009. "The quality of monetary policy and inflation performance: globalization and its aftermath," Bank of Finland Research Discussion Papers 31/2009, Bank of Finland.
    61. Sebastian Dullien & Ulrich Fritsche, 2007. "Anhaltende Divergenz bei Inflations- und Lohnentwicklung in der Eurozone: Gefahr für die Währungsunion?," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 76(4), pages 56-76.
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    63. Boysen-Hogrefe, Jens & Dovern, Jonas & Gern, Klaus-Jürgen & Meier, Carsten-Patrick & Scheide, Joachim, 2010. "Schwache Konjunktur im Euroraum: Nur langsamer Abbau der Ungleichgewichte," Open Access Publications from Kiel Institute for the World Economy 45583, Kiel Institute for the World Economy (IfW Kiel).
    64. Alina M. Spiru, 2008. "Inflation Convergence In Central And Eastern European Economies," Romanian Economic Business Review, Romanian-American University, vol. 3(4), pages 14-34, Winter.
    65. Hakan Yilmazkuday, 2022. "Inflation convergence over time: Sector‐level evidence within Europe," International Finance, Wiley Blackwell, vol. 25(2), pages 183-217, August.
    66. Troy Lorde & Winston Moore, 2008. "Co-Movement in Tourist Arrivals in the Caribbean," Tourism Economics, , vol. 14(3), pages 631-643, September.
    67. Liontakis, Angelos E. & Papadas, Christos T., 2009. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," 113th Seminar, September 3-6, 2009, Chania, Crete, Greece 58084, European Association of Agricultural Economists.
    68. Stephen Hall & Sérgio Lagoa, 2014. "Inflation and Business Cycle Convergence in the Euro Area: Empirical Analysis Using an Unobserved Component Model," Open Economies Review, Springer, vol. 25(5), pages 885-908, November.
    69. Omid M. Ardakani & N. Kundan Kishor & Suyong Song, 2024. "Does membership of the EMU matter for economic and financial outcomes?," Contemporary Economic Policy, Western Economic Association International, vol. 42(3), pages 416-447, July.
    70. Stefano IACUS & Giuseppe PORRO, 2013. "Does European Monetary Union make inflation dynamics more uniform?," Departmental Working Papers 2013-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    71. Alberto Montagnoli & Andros Gregoriou & Alexandros Kontonikas, 2007. "Euro Area Inflation Differentials: Unit Roots, Structural Breaks and Non-Linear Adjustment," Working Papers 2007_13, Business School - Economics, University of Glasgow.
    72. PIROVANO, Mara & VAN POECK, André, 2011. "Eurozone inflation differentials and the ECB," Working Papers 2011014, University of Antwerp, Faculty of Business and Economics.
    73. Marianna Riggi & Fabrizio Venditti, 2014. "Surprise! Euro area inflation has fallen," Questioni di Economia e Finanza (Occasional Papers) 237, Bank of Italy, Economic Research and International Relations Area.
    74. Abban, Stanley, 2020. "On the Computation and Essence of the Nominal Convergence Criteria for Africa Currency Union: ECOWAS in Perspective," MPRA Paper 100215, University Library of Munich, Germany, revised 10 May 2020.
    75. Maria Tsafa-Karakatsanidou & Stilianos Fountas, 2018. "Testing for Inflation Convergence Among European Union Countries: A Panel Approach," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 64(1), pages 17-37.
    76. IALOMITIANU Razvan Gheorghe & BOLDEANU Teodor Florin, 2017. "Romania And The Euro. An Overview Of Maastricht Convergence Criteria Fulfillment," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(1), pages 74-87, April.
    77. 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.
    78. Libero Monteforte & Stefano Siviero, 2010. "The economic consequences of euro-area macro-modelling shortcuts," Applied Economics, Taylor & Francis Journals, vol. 42(19), pages 2399-2415.
    79. Juan Carlos Cuestas & Luis A. Gil-Alana & Karl Taylor, 2012. "Inflation Convergence in Central and Eastern Europe with a View to Adopting the Euro," Working Papers 2012005, The University of Sheffield, Department of Economics.
    80. 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.
    81. Baskaran, Thushyanthan, 2009. "Did the Maastricht treaty matter for macroeconomic performance?," MPRA Paper 30106, University Library of Munich, Germany.
    82. Pilbeam, K. & Litsios, I., 2015. "An Empirical Analysis of the Nexus between Investment, Fiscal Balances and Current Account Balances in Greece, Portugal and Spain," Working Papers 15/18, Department of Economics, City University London.
    83. Sebastian Dullien & Ulrich Fritsche, 2007. "Does the Dispersion of Unit Labor Cost Dynamics in the EMU Imply Long-run Divergence? Results from a Comparison with the United States of America and Germany," Macroeconomics and Finance Series 200702, University of Hamburg, Department of Socioeconomics.
    84. Emmanuel Anoruo & Vasudeva N.R. Murthy, 2014. "Testing Nonlinear Inflation Convergence for the Central African Economic and Monetary Community," International Journal of Economics and Financial Issues, Econjournals, vol. 4(1), pages 1-7.
    85. Svetlana Makarova, 2016. "ECB footprints on inflation forecast uncertainty," Bank of Estonia Working Papers wp2016-5, Bank of Estonia, revised 19 Jul 2016.
    86. Michele Caputo & Francesco Forte, 2015. "Difficult Convergence among the Five Main European Union Countries and the Crisis of the Euro Area," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 43(4), pages 415-430, December.
    87. Jean-Baptiste Nkume, 2014. "Optimal Inflation Threshold for Economic Growth in Malawi," Journal of Economics and Behavioral Studies, AMH International, vol. 6(12), pages 933-946.
    88. Nagayasu, Jun, 2012. "Regional inflation and industrial structure in monetary union," MPRA Paper 37310, University Library of Munich, Germany.
    89. Hałka, Aleksandra & Leszczyńska-Paczesna, Agnieszka, 2019. "Price convergence in the European Union – What has changed?," Economic Modelling, Elsevier, vol. 79(C), pages 226-241.
    90. Kamiar Mohaddes & Oral H. Williams, 2013. "Inflation Differentials In The Gcc: Does The Oil Cycle Matter?," Middle East Development Journal (MEDJ), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-23.
    91. Delle Monache & Ivan Petrella & Fabrizio Venditti, 2015. "Common faith or parting ways? A time varying parameters factor analysis of euro-area inflation," Birkbeck Working Papers in Economics and Finance 1515, Birkbeck, Department of Economics, Mathematics & Statistics.
    92. Melike Ecem Sertbaş, 2019. "The Analysis of Convergence of Inflation Rates of Goods and Services with General Inflation Rates in the Turkish Economy," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 30(0), pages 21-31, June.
    93. Giulio PALOMBA & Emma SARNO & Alberto ZAZZARO, 2007. "Testing similarities of short-run inflation dynamics among EU countries after the Euro," Working Papers 289, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    94. Pietro Cova & Lisa Rodano, 2019. "Relative price dynamics in the Euro area: where do we stand?," Temi di discussione (Economic working papers) 1226, Bank of Italy, Economic Research and International Relations Area.
    95. Mr. Ashoka Mody & Ms. Franziska L Ohnsorge, 2007. "Can Domestic Policies Influence Inflation?," IMF Working Papers 2007/257, International Monetary Fund.
    96. Carlos Esteban Posada Posada & Wilman Gómez & Remberto Rhenals, 2021. "Caída y convergencia mundial de las tasas de inflación," Documentos de Trabajo de Valor Público 19129, Universidad EAFIT.
    97. Svetlana Makarova, 2018. "European Central Bank Footprints On Inflation Forecast Uncertainty," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 637-652, January.
    98. André Van Poeck, 2010. "One Money and Sixteen Needs: Has the ECB’s Monetary Policy Become More Balanced Towards the Needs of the Member States?," De Economist, Springer, vol. 158(1), pages 43-60, April.
    99. Cavallero, Alessandro, 2011. "The convergence of inflation rates in the EU-12 area: A distribution dynamics approach," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 341-357, June.
    100. Yilmazkuday, Hakan, 2009. "Inflation Targeting and Inflation Convergence within Turkey," MPRA Paper 16770, University Library of Munich, Germany.
    101. Christian Proaño Acosta, 2007. "Inflation Differentials and Business Cycle Fluctuations in the European Monetary Union," IMK Working Paper 05-2007, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    102. Ahlgren, Niklas & Juselius, Mikael, 2009. "Tests for Cointegration Rank and the Initial Condition," Working Papers 539, Hanken School of Economics.
    103. GRENADE, Kari & MOORE, Winston, 2008. "Co-Movements Between Foreign And Domestic Interest Rates In A Fixed Exchange Rate Regime: The Case Of The Eccu And The Us," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 8(1), pages 119-130.
    104. Juan Carlos Cuestas & Luis A. Gil-Alana & Karl Taylor, 2016. "Inflation convergence in Central and Eastern Europe vs. the Eurozone: Non-linearities and long memory," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(5), pages 519-538, November.
    105. Tirtosuharto, Darius & Adiwilaga, Handri, 2013. "Decentralization and Regional Inflation in Indonesia," MPRA Paper 70691, University Library of Munich, Germany.
    106. Afflatet, Nicolas, 2014. "European Monetary Policy in the Heterogeneous Currency Area and the Open Question of Convergence," EconStor Preprints 93382, ZBW - Leibniz Information Centre for Economics.
    107. Siklos, Pierre L., 2010. "Meeting Maastricht: Nominal convergence of the new member states toward EMU," Economic Modelling, Elsevier, vol. 27(2), pages 507-515, March.
    108. VAN POECK, André, 2009. "One money and fifteen needs inflation and output convergence in the European Monetary Union," Working Papers 2009001, University of Antwerp, Faculty of Business and Economics.
    109. Alina M. Spiru, 2008. "Inflation Convergence In Central And Eastern European Economies," Journal of Information Systems & Operations Management, Romanian-American University, vol. 2(1), pages 289-316, July.
    110. Liu, Tie-Ying & Lee, Chien-Chiang, 2021. "Global convergence of inflation rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    111. Harold James, 2017. "The contribution of monetary institutions to stability," Aussenwirtschaft, University of St. Gallen, School of Economics and Political Science, Swiss Institute for International Economics and Applied Economics Research, vol. 68(01), pages 1-18, December.
    112. Sandeep Mazumder, 2014. "European Monetary Union and the Cost of Disinflation," Economic Issues Journal Articles, Economic Issues, vol. 19(2), pages 1-20, September.
    113. Nima Nonejad, 2019. "Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 246-276, May.
    114. Hualde, Javier & Iacone, Fabrizio, 2017. "Revisiting inflation in the euro area allowing for long memory," Economics Letters, Elsevier, vol. 156(C), pages 145-150.
    115. Barrett, Alan & Bergin, Adele & FitzGerald, John & Traistaru-Siedschlag, Iulia, 2006. "Economic Assessment of the Euro Area: Forecasts and Policy Analysis, Autumn Report 2006," Research Series, Economic and Social Research Institute (ESRI), number sustat22.
    116. Maurer, Rainer, 2022. "Price levels in the European Monetary Union: Even tradables follow independent random walks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    117. TRIANDAFIL, Cristina Maria, 2013. "Sustainability of convergence in the context of macro-prudential policies in the European Union," Working Papers of National Institute for Economic Research 130618, Institutul National de Cercetari Economice (INCE).
    118. Eichler, Stefan & Hielscher, Kai, 2012. "Does the ECB act as a lender of last resort during the subprime lending crisis?: Evidence from monetary policy reaction models," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 552-568.

  26. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergences of prices and rates of inflation," Temi di discussione (Economic working papers) 575, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Nagayasu, Jun, 2014. "Regional inflation, spatial location and the Balassa-Samuelson effect," MPRA Paper 59220, University Library of Munich, Germany.
    2. Huang, Ho-Chuan (River) & Liu, Wei-Han & Yeh, Chih-Chuan, 2012. "Convergence in price levels across US cities," Economics Letters, Elsevier, vol. 114(3), pages 245-248.
    3. Garcia-Hiernaux, Alfredo & Guerrero, David E., 2021. "Price convergence: Representation and testing," Economic Modelling, Elsevier, vol. 104(C).
    4. Andrea Vaona & Guido Ascari, 2012. "Regional Inflation Persistence: Evidence from Italy," Regional Studies, Taylor & Francis Journals, vol. 46(4), pages 509-523, June.
    5. Busetti, Fabio, 2009. "Initial conditions and stationarity tests," Economics Letters, Elsevier, vol. 105(3), pages 296-299, December.
    6. Hiranya K. Nath & Jayanta Sarkar, 2014. "City Relative Price Dynamics in Australia: Are Structural Breaks Important?," The Economic Record, The Economic Society of Australia, vol. 90(288), pages 33-48, March.
    7. Garcia-Hiernaux, Alfredo & Gonzalez-Perez, Maria T. & Guerrero, David E., 2023. "Eurozone prices: A tale of convergence and divergence," Economic Modelling, Elsevier, vol. 126(C).
    8. Diego Winkelried & José Enrique Gutierrez, 2015. "Regional Inflation Dynamics and Inflation Targeting. The Case of Peru," Journal of Applied Economics, Taylor & Francis Journals, vol. 18(2), pages 199-224, November.
    9. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    10. Arestis, Philip & Chortareas, Georgios & Magkonis, Georgios & Moschos, Demetrios, 2014. "Inflation targeting and inflation convergence: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 285-295.
    11. Alejandro C. García-Cintado & Diego Romero-Ávila & Carlos Usabiaga, 2016. "The economic integration of Spain: a change in the inflation pattern," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 25(1), pages 1-41, December.
    12. Sauro Mocetti, 2012. "Educational choices and the selection process: before and after compulsory schooling," Education Economics, Taylor & Francis Journals, vol. 20(2), pages 189-209, February.
    13. Elena Pesavento, Barbara Rossi, 2006. "Impulse Response Confidence Intervals for Persistent Data: What Have We Learned?," Economics Working Papers ECO2006/19, European University Institute.
    14. Alfredo García Hiernaux & David Esteban Guerrero Burbano, 2015. "Price-Level Convergence in the Eurozone," Documentos de Trabajo del ICAE 2015-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    15. Carla Massidda & Paolo Mattana, 2008. "Regional productivity and relative prices dynamics: the case of Italy," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(4), pages 945-966, December.
    16. Winkelried, Diego & Gutiérrez, José, 2012. "Dinámica inflacionaria regional y el esquema de metas de inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 24, pages 79-98.
    17. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
    18. Angelos Liontakis & Christos T. Papadas, 2010. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," Working Papers 2010-6, Agricultural University of Athens, Department Of Agricultural Economics.
    19. Dreger Christian & Kosfeld Reinhold, 2010. "Do Regional Price Levels Converge?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(3), pages 274-286, June.
    20. Adebola, Solarin Sakiru & Gil-Alana, Luis A. & Madigu, Godfrey, 2019. "Gold prices and the cryptocurrencies: Evidence of convergence and cointegration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1227-1236.
    21. Liontakis, Angelos E. & Papadas, Christos T., 2009. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," 113th Seminar, September 3-6, 2009, Chania, Crete, Greece 58084, European Association of Agricultural Economists.
    22. Guglielmo Caporale & Burcu Erdogan & Vladimir Kuzin, 2015. "Testing stock market convergence: a non-linear factor approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 481-498, August.
    23. Carlos Carrasco & Jesus Ferreiro, 2013. "Inflation targeting in Mexico," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 35(3), pages 341-372.
    24. Kosfeld, Reinhold & Eckey, Hans-Friedrich & Lauridsen, Jørgen, 2007. "Disparities in prices and income across German NUTS 3 regions," Volkswirtschaftliche Diskussionsbeiträge 93, University of Kassel, Faculty of Economics and Management.
    25. 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.
    26. Winkelried, Diego & Gutierrez, José Enrique, 2012. "Regional inflation dynamics and inflation targeting in Peru," Working Papers 2012-018, Banco Central de Reserva del Perú.
    27. Delle Monache & Ivan Petrella & Fabrizio Venditti, 2015. "Common faith or parting ways? A time varying parameters factor analysis of euro-area inflation," Birkbeck Working Papers in Economics and Finance 1515, Birkbeck, Department of Economics, Mathematics & Statistics.
    28. Ailenei, Dorel & Cristescu, Amalia, 2010. "Regional Distribution of Inflationary Pressures in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 32-43, December.
    29. Matteo Bugamelli & Alfonso Rosolia, 2006. "Productivity and foreign competition," Temi di discussione (Economic working papers) 578, Bank of Italy, Economic Research and International Relations Area.
    30. Christian Dreger & Reinhold Kosfeld, 2007. "Do Regional Price Levels Converge?: Paneleconometric Evidence Based on German Districts," Discussion Papers of DIW Berlin 754, DIW Berlin, German Institute for Economic Research.
    31. Yilmazkuday, Hakan, 2009. "Inflation Targeting and Inflation Convergence within Turkey," MPRA Paper 16770, University Library of Munich, Germany.
    32. Jun Nagayasu, 2017. "Regional inflation, spatial locations and the Balassa-Samuelson effect: Evidence from Japan," Urban Studies, Urban Studies Journal Limited, vol. 54(6), pages 1482-1499, May.
    33. David Gray, 2021. "A simple measure of beta-convergence revisited," Urban Studies, Urban Studies Journal Limited, vol. 58(12), pages 2569-2583, September.

  27. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2005. "Trends and cycles in economic time series: A Bayesian approach," Econometric Institute Research Papers EI 2005-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Planas, C. & Roeger, W. & Rossi, A., 2013. "The information content of capacity utilization for detrending total factor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 577-590.
    2. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    3. Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    5. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. D.S. Prasada Rao & Alicia Rambaldi & Howard Doran, 2008. "A Method to Construct World Tables of Purchasing Power Parities and Real Incomes Based on Multiple Benchmarks and Auxiliary Information: Analytical and Empirical Results," CEPA Working Papers Series WP052008, School of Economics, University of Queensland, Australia.
    7. Kauermann Goeran & Krivobokova Tatyana & Semmler Willi, 2011. "Filtering Time Series with Penalized Splines," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-28, March.
    8. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    9. Macaro, Christian, 2010. "Bayesian non-parametric signal extraction for Gaussian time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 381-395, August.
    10. Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2006. "Real Time Representation of the UK Output Gap in the Presence of Trend Uncertainty," Birkbeck Working Papers in Economics and Finance 0618, Birkbeck, Department of Economics, Mathematics & Statistics.
    11. Trimbur, Thomas M., 2010. "Stochastic level shifts and outliers and the dynamics of oil price movements," International Journal of Forecasting, Elsevier, vol. 26(1), pages 162-179, January.
    12. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    13. Łukasz Lenart & Mateusz Pipień, 2017. "Non-Parametric Test for the Existence of the Common Deterministic Cycle: The Case of the Selected European Countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 201-241, September.
    14. Gonzalez, Rodrigo Barbone & Marinho, Leonardo Sousa Gomes & Lima, Joaquim Ignacio Alves de Vasconcellos e, 2017. "Re-anchoring countercyclical capital buffers: Bayesian estimates and alternatives focusing on credit growth," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1007-1024.
    15. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    16. Antonio Bassanetti & Michele Caivano & Alberto Locarno, 2013. "Modelling italian potential output and the output gap," Working Papers 7, Department of the Treasury, Ministry of the Economy and of Finance.
    17. Alban Moura, 2022. "Why you should never use the Hodrick-Prescott Filter: Comment," BCL working papers 162, Central Bank of Luxembourg.
    18. Alicia N. Rambaldi & D.S. Prasada Rao & K. Renuka Ganegodage, 2009. "Spatial Autocorrelation and Extrapolation of Purchasing Power Parities. Modelling and Sensitivity Analysis," CEPA Working Papers Series WP012009, School of Economics, University of Queensland, Australia.
    19. Soloschenko, Max & Weber, Enzo, 2012. "Trend-Cycle Interactions and the Subprime Crisis: Analysis of US and Canadian Output," University of Regensburg Working Papers in Business, Economics and Management Information Systems 470, University of Regensburg, Department of Economics.
    20. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    21. Warapong Wongwachara & Anusorn Minphimai, 2009. "Unobserved Component Models of the Phillips Relation in the ASEAN Economy," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 5(2), pages 241-256, July.
    22. Mihnea Constantinescu & Anh Dinh Minh Nguyen, 2017. "Unemployment or Credit: Who Holds The Potential? Results From a Small-Open Economy," Bank of Lithuania Discussion Paper Series 4, Bank of Lithuania.
    23. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    24. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.
    25. Yang, Jinyu & Dong, Dayong & Liang, Chao, 2024. "Climate policy uncertainty and the U.S. economic cycle," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    26. Mendelssohn, Roy, 2011. "The STAMP Software for State Space Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i02).
    27. James M. Nason & John H. Rogers, 2008. "Exchange rates and fundamentals: a generalization," International Finance Discussion Papers 948, Board of Governors of the Federal Reserve System (U.S.).
    28. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
    29. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    30. R. Dixon & G. Lim, 2012. "A univariate model of aggregate labour productivity," Applied Economics, Taylor & Francis Journals, vol. 44(5), pages 581-585, February.
    31. James Morley & Irina B Panovska, 2016. "Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?," Discussion Papers 2016-12, School of Economics, The University of New South Wales.
    32. Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
    33. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    34. Constantinescu, Mihnea & Nguyen, Anh D.M., 2018. "Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization," Economic Systems, Elsevier, vol. 42(4), pages 649-664.
    35. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    36. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
    37. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    38. Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
    39. Takahiro Yabe & Yunchang Zhang & Satish Ukkusuri, 2020. "Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach," Papers 2004.11121, arXiv.org.
    40. Bernardi Mauro & Della Corte Giuseppe & Proietti Tommaso, 2011. "Extracting the Cyclical Component in Hours Worked," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-28, May.
    41. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    42. Christophe Planas & Alessandro Rossi & Gabriele Fiorentini, 2008. "The marginal likelihood of Structural Time Series Models, with application to the euro area and US NAIRU," Working Paper series 21_08, Rimini Centre for Economic Analysis.
    43. Christoph F. Kurz & Martin Rehm & Rolf Holle & Christina Teuner & Michael Laxy & Larissa Schwarzkopf, 2019. "The effect of bariatric surgery on health care costs: A synthetic control approach using Bayesian structural time series," Health Economics, John Wiley & Sons, Ltd., vol. 28(11), pages 1293-1307, November.
    44. Rob Luginbuhl, 2020. "Estimation of the Financial Cycle with a Rank-Reduced Multivariate State-Space Model," CPB Discussion Paper 409, CPB Netherlands Bureau for Economic Policy Analysis.
    45. Garratt, Anthony & Lee, Kevin & Mise, Emi & Shields, Kalvinder, 2009. "Real time representation of the UK output gap in the presence of model uncertainty," International Journal of Forecasting, Elsevier, vol. 25(1), pages 81-102.
    46. Andrew Harvey, 2011. "Modelling the Phillips curve with unobserved components," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 7-17.
    47. Paolo Guarda & Alban Moura, 2019. "Measuring real and financial cycles in Luxembourg: An unobserved components approach," BCL working papers 126, Central Bank of Luxembourg.
    48. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    49. Tim Willems, 2009. "Visualizing the Invisible: Estimating the New Keynesian Output Gap via a Bayesian Approach," Tinbergen Institute Discussion Papers 09-074/2, Tinbergen Institute, revised 26 Mar 2010.
    50. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    51. Yasutomo Murasawa, 2014. "Measuring the natural rates, gaps, and deviation cycles," Empirical Economics, Springer, vol. 47(2), pages 495-522, September.
    52. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Business and Financial Cycles: an estimation of cycles’ length focusing on Macroprudential Policy," Working Papers Series 385, Central Bank of Brazil, Research Department.
    53. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    54. 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.
    55. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
    56. Michael O’Grady, 2019. "Estimating the Output, Inflation and Unemployment Gaps in Ireland using Bayesian Model Averaging," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 35-76.
    57. Łukasz Lenart, 2018. "Bayesian inference for deterministic cycle with time-varying amplitude: the case of growth cycle in European countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(3), pages 233-262, September.
    58. Reusens Peter & Croux Christophe, 2017. "Detecting time variation in the price puzzle: a less informative prior choice for time varying parameter VAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    59. James Morley, 2014. "Measuring Economic Slack: A Forecast-Based Approach with Applications to Economies in Asia and the Pacific," BIS Working Papers 451, Bank for International Settlements.
    60. Nashimoto, Kane & Wright, F.T., 2008. "Bayesian multiple comparisons of simply ordered means using priors with a point mass," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5143-5153, August.
    61. Andrew Harvey, 2010. "The local quadratic trend model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 94-108.
    62. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    63. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Countercyclical Capital Buffers: bayesian estimates and alternatives focusing on credit growth," Working Papers Series 384, Central Bank of Brazil, Research Department.
    64. Ekici, Oya & Nemlioğlu, Karun, 2017. "Emerging economies’ short-term private external debt as evidence of economic crisis," Journal of Policy Modeling, Elsevier, vol. 39(2), pages 232-246.

  28. Harvey, Andrew & Carvalho, Vasco, 2004. "Convergence and Cycles in the Euro Zone," CEPR Discussion Papers 4726, C.E.P.R. Discussion Papers.

    Cited by:

    1. James H. Stock & Mark W. Watson, 2003. "Understanding Changes in International Business Cycle Dynamics," NBER Working Papers 9859, National Bureau of Economic Research, Inc.
    2. James H. Stock & Mark W. Watson, 2003. "Has the business cycle changed?," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 9-56.
    3. W. Jos Jansen & Ad C.J. Stokman, 2004. "Foreign Direct Investment and International Business Cycle Comovement," Macroeconomics 0402029, University Library of Munich, Germany.
    4. Maurizio Bovi, 2003. "Nonparametric Analysis Of The International Business Cycles," ISAE Working Papers 37, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    5. Bovi, M., 2005. "Economic Clubs and European Commitment. Evidence from the International Business Cycles," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(2), pages 101-122.
    6. Eickmeier, Sandra, 2005. "Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model," Discussion Paper Series 1: Economic Studies 2005,02, Deutsche Bundesbank.

  29. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Ferroni, Filippo, 2009. "Trend agnostic one step estimation of DSGE models," MPRA Paper 14550, University Library of Munich, Germany.
    2. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2005. "Trends and cycles in economic time series: A Bayesian approach," Econometric Institute Research Papers EI 2005-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  30. Andrew Harvey, 2004. "Trend estimation, signal-noise ratios and the frequency of observations," Econometric Society 2004 Australasian Meetings 343, Econometric Society.

    Cited by:

    1. Alessandra Iacobucci & Alain Noullez, 2004. "A Frequency Selective Filter for Short-Length Time Series," Documents de Travail de l'OFCE 2004-05, Observatoire Francais des Conjonctures Economiques (OFCE).
    2. Tucker S. McElroy & Thomas M. Trimbur, 2007. "Continuous time extraction of a nonstationary signal with illustrations in continuous low-pass and band-pass filtering," Finance and Economics Discussion Series 2007-68, Board of Governors of the Federal Reserve System (U.S.).

  31. Harvey, A. & TTrimbur, T. & van Dijk, H., 2003. "Cyclical Components in Economic Time Series: a Bayesian Approach," Cambridge Working Papers in Economics 0302, Faculty of Economics, University of Cambridge.

    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. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.
    3. Martha López P., 2003. "Efficient Policy Rule for Inflation Targeting in Colombia," Borradores de Economia 240, Banco de la Republica de Colombia.
    4. Luis Gonzalo Llosa & Shirley Miller, 2004. "Using Additional Information in Estimating the Output Gap in Peru: a Multivariate Unobserved Component Approach," Money Affairs, CEMLA, vol. 0(1), pages 57-82, January-J.
    5. Wayne Robinson, 2004. "Real Shocks, Credibility & Stabilization Policy in a Small Open Economy," Money Affairs, CEMLA, vol. 0(1), pages 39-55, January-J.
    6. Adriana Arreaza & Enid Blanco & Miguel Dorta, 2004. "A Small Scale Macroeconomic Model for Venezuela," Money Affairs, CEMLA, vol. 0(1), pages 25-38, January-J.
    7. Harm Bandholz & Gebhard Flaig & Johannes Mayr, 2005. "Wachstum und Konjunktur in OECD-Ländern: Eine langfristige Perspektive," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(04), pages 28-36, February.
    8. Thomas M. Trimbur, 2006. "Properties of higher order stochastic cycles," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(1), pages 1-17, January.

  32. Harvey, A. & Bates, D., 2003. "Multivariate Unit Root Tests and Testing for Convergence," Cambridge Working Papers in Economics 0301, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    2. Usman Khalid & Luke Okafor & Muhammad Shahbaz, 2022. "Economic reform and political stagnation: The inconsistent patterns of institutional change," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(4), pages 813-844, October.
    3. Busetti, Fabio & Forni, Lorenzo & Harvey, Andrew & Venditti, Fabrizio, 2006. "Inflation convergence and divergence within the European Monetary Union," Working Paper Series 574, European Central Bank.
    4. 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.
    5. Pesaran, M.H., 2003. "A Simple Panel Unit Root Test in the Presence of Cross Section Dependence," Cambridge Working Papers in Economics 0346, Faculty of Economics, University of Cambridge.
    6. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    7. 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.
    8. Elliott, Graham & Muller, Ulrich K., 2006. "Minimizing the impact of the initial condition on testing for unit roots," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 285-310.
    9. Kristian Jönsson, 2005. "Cross‐sectional Dependency and Size Distortion in a Small‐sample Homogeneous Panel Data Unit Root Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(3), pages 369-392, June.
    10. Sandra Eickmeier, 2009. "Comovements and heterogeneity in the euro area analyzed in a non-stationary dynamic factor model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 933-959.
    11. Johan Lyhagen & Johanna Rickne, 2014. "Income inequality between Chinese regions: newfound harmony or continued discord?," Empirical Economics, Springer, vol. 47(1), pages 93-110, August.
    12. Joerg Breitung & M. Hashem Pesaran, 2005. "Unit Roots and Cointegration in Panels," CESifo Working Paper Series 1565, CESifo.
    13. Christophe Hurlin & V. Mignon, 2005. "Une Synthèse des Tests de Racine Unitaire en sur Données de Panel," Post-Print halshs-00257324, HAL.
    14. Alina M. Spiru, 2008. "Inflation Convergence In Central And Eastern European Economies," Romanian Economic Business Review, Romanian-American University, vol. 3(4), pages 14-34, Winter.
    15. Troy Lorde & Winston Moore, 2008. "Co-Movement in Tourist Arrivals in the Caribbean," Tourism Economics, , vol. 14(3), pages 631-643, September.
    16. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.
    17. Usman Khalid, 2016. "Catch-up in Institutional Quality: An Empirical Assessment," Discussion Papers 2016-04, University of Nottingham, CREDIT.
    18. Fischer, Christoph, 2007. "An assessment of the trends in international price competitiveness among EMU countries," Discussion Paper Series 1: Economic Studies 2007,08, Deutsche Bundesbank.
    19. Fabio Busetti & Michele Caivano, 2017. "Low frequency drivers of the real interest rate: a band spectrum regression approach," Temi di discussione (Economic working papers) 1132, Bank of Italy, Economic Research and International Relations Area.
    20. Lorenzo Lucchese & Mikko Pakkanen & Almut Veraart, 2022. "The Short-Term Predictability of Returns in Order Book Markets: a Deep Learning Perspective," Papers 2211.13777, arXiv.org, revised Oct 2023.
    21. Ghassen El Montasser & Roula Inglesi-Lotz & Rangan Gupta, 2013. "Convergence of Greenhouse Gas Emissions among G7 Countries," Working Papers 201386, University of Pretoria, Department of Economics.
    22. GRENADE, Kari & MOORE, Winston, 2008. "Co-Movements Between Foreign And Domestic Interest Rates In A Fixed Exchange Rate Regime: The Case Of The Eccu And The Us," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 8(1), pages 119-130.
    23. Christoph Fischer & Daniel Porath, 2010. "A reappraisal of the evidence on PPP: a systematic investigation into MA roots in panel unit root tests and their implications," Empirical Economics, Springer, vol. 39(3), pages 767-792, December.
    24. Alina M. Spiru, 2008. "Inflation Convergence In Central And Eastern European Economies," Journal of Information Systems & Operations Management, Romanian-American University, vol. 2(1), pages 289-316, July.

  33. Vasco M.Carvalho & Andrew C.Harvey, 2002. "Growth, Cycles and Convergence in US Regional Time Series," Cambridge Working Papers in Economics 0221, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Lo Cascio, Iolanda, 2021. "A wavelet analysis of the ripple effect in UK regional housing markets," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1093-1105.
    2. Miles, William, 2020. "Regional convergence-and divergence-in the US," Research in Economics, Elsevier, vol. 74(2), pages 131-139.
    3. Usman Khalid & Luke Okafor & Muhammad Shahbaz, 2022. "Economic reform and political stagnation: The inconsistent patterns of institutional change," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(4), pages 813-844, October.
    4. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    5. Andrés Rodríguez-Pose & Ugo Fratesi, 2006. "Regional business cycles and the emergence of sheltered economies in the southern periphery of Europe," Bruges European Economic Research Papers 7, European Economic Studies Department, College of Europe.
    6. Holger Breinlich & Gianmarco I. P. Ottaviano & Jonathan R. W. Temple, 2013. "Regional Growth and Regional Decline," CEP Discussion Papers dp1232, Centre for Economic Performance, LSE.
    7. Mihai Nica, 2004. "Convergence in Mississippi: A Spatial Approach," Urban/Regional 0408007, University Library of Munich, Germany.
    8. 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.
    9. Magdalena Osinska & Karolina Kluth, 2010. "Convergence of Greek Economy with the EU and Some Comparisons with Polish Experience," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 139-156.
    10. William Miles, 2015. "Regional House Price Segmentation and Convergence in the US: A New Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(1), pages 113-128, January.
    11. David Gray, 2018. "An application of two non-parametric techniques to the prices of British dwellings: An examination of cyclicality," Urban Studies, Urban Studies Journal Limited, vol. 55(10), pages 2286-2299, August.
    12. Dimitris, Chrsitopoulos & Miguel, Leon-Ledesma, 2009. "International Output Convergence, Breaks, and Asymmetric Adjustment," MPRA Paper 14566, University Library of Munich, Germany.
    13. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    14. Miles, William, 2020. "House price convergence in the euro zone: A pairwise approach," Economic Systems, Elsevier, vol. 44(3).
    15. Roberto Basile & Sergio de Nardis & Carmine Pappalardo, 2012. "Firm Heterogeneity and Regional Business Cycles Differentials," ERSA conference papers ersa12p84, European Regional Science Association.
    16. Johan Lyhagen & Johanna Rickne, 2014. "Income inequality between Chinese regions: newfound harmony or continued discord?," Empirical Economics, Springer, vol. 47(1), pages 93-110, August.
    17. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    18. 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.
    19. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.
    20. Kiyotaka Sato & Junko Shimizu & Nagendra Shrestha & Shajuan Zhang, 2013. "Industry-specific Real Effective Exchange Rates and Export Price Competitiveness: The Cases of Japan, China, and Korea," Asian Economic Policy Review, Japan Center for Economic Research, vol. 8(2), pages 298-321, December.
    21. Usman Khalid, 2016. "Catch-up in Institutional Quality: An Empirical Assessment," Discussion Papers 2016-04, University of Nottingham, CREDIT.
    22. 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.
    23. Robert Dixon, 2007. "Common Cycles in Labour Market Separation Rates for Australian States," Department of Economics - Working Papers Series 991, The University of Melbourne.
    24. Magrini, Stefano, 2004. "Regional (di)convergence," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 62, pages 2741-2796, Elsevier.
    25. Bernardina Algieri, 2015. "Price and non-price competitiveness in export demand: empirical evidence from Italy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 157-183, February.

  34. Busettti, F. & Harvey, A., 2002. "Testing for Drift in a Time Series," Cambridge Working Papers in Economics 0237, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    2. Busetti, Fabio & Harvey, Andrew, 2008. "Testing For Trend," Econometric Theory, Cambridge University Press, vol. 24(1), pages 72-87, February.

  35. Andrew Harvey, 2002. "Trends, Cycles and Convergence," Working Papers Central Bank of Chile 155, Central Bank of Chile.

    Cited by:

    1. 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.
    2. Lavan Mahadeva and Paul Robinson, 2004. "Unit Root Testing in a Central Bank," Handbooks, Centre for Central Banking Studies, Bank of England, number 22, April.

  36. Harvey, A. & Vasco Carvalho, 2002. "Models for Converging Economies," Cambridge Working Papers in Economics 0216, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2002. "The European Business Cycle," Economic Working Papers at Centro de Estudios Andaluces E2002/19, Centro de Estudios Andaluces.
    2. Busetti, Fabio & Forni, Lorenzo & Harvey, Andrew & Venditti, Fabrizio, 2006. "Inflation convergence and divergence within the European Monetary Union," Working Paper Series 574, European Central Bank.
    3. Loayza, Norman V. & Meller, Patricio, 2003. "Comments," LSE Research Online Documents on Economics 123335, London School of Economics and Political Science, LSE Library.
    4. 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.
    5. Rob Luginbuhl & Siem Jan Koopman, 2003. "Convergence in European GDP Series," Tinbergen Institute Discussion Papers 03-031/4, Tinbergen Institute.
    6. Rob Luginbuhl & Siem Jan Koopman, 2004. "Convergence in European GDP series: a multivariate common converging trend-cycle decomposition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 611-636.
    7. 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.
    8. Haldrup, Niels, "undated". "Empirical analysis of price data in the delineation of the relevant geographical market in competition analysis," Economics Working Papers 2003-9, Department of Economics and Business Economics, Aarhus University.
    9. 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.
    10. Andrew C. Harvey, 2002. "Trends, Cycles, and Convergence," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.),Economic Growth: Sources, Trends, and Cycles, edition 1, volume 6, chapter 8, pages 221-250, Central Bank of Chile.
    11. Christian Proaño Acosta, 2007. "Inflation Differentials and Business Cycle Fluctuations in the European Monetary Union," IMK Working Paper 05-2007, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    12. Magrini, Stefano, 2004. "Regional (di)convergence," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 62, pages 2741-2796, Elsevier.

  37. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2002. "Cyclical components in economic time series," Econometric Institute Research Papers EI 2002-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    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. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.
    3. Harm Bandholz & Gebhard Flaig & Johannes Mayr, 2005. "Wachstum und Konjunktur in OECD-Ländern: Eine langfristige Perspektive," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(04), pages 28-36, February.
    4. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  38. Harvey, A.C. & Trimbur, T.M., 2001. "General Model-based Filters for Extracting Cycles and Trends in Economic Time Series," Cambridge Working Papers in Economics 0113, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bashar, Omar H.M.N. & Bhattacharya, Prasad Sankar & Wohar, Mark E., 2017. "The cyclicality of fiscal policy: New evidence from unobserved components approach," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 222-234.
    2. João Valle e Azevedo & Ana Pereira, 2008. "Approximating and Forecasting Macroeconomic Signals in Real-Time," Working Papers w200819, Banco de Portugal, Economics and Research Department.
    3. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    4. Ahmed Belhadjayed & Grégoire Loeper & Frédéric Abergel, 2016. "Forecasting Trends With Asset Prices," Post-Print hal-01512431, HAL.
    5. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
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    142. Proietti, Tommaso, 2005. "New algorithms for dating the business cycle," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 477-498, April.
    143. Dilip Nachane & Aditi Chaubal, 2022. "A Comparative Evaluation of Some DSP Filters vis-à-vis Commonly Used Economic Filters," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 161-190, September.
    144. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    145. Li, Yunhan & Shonkwiler, J. Scott, 2021. "The Vanishing U.S. Cattle Cycle: A Stochastic Cycle Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 46(3), September.
    146. Tommaso Proietti & Alessandra Luati, 2013. "Generalised Linear Spectral Models," CEIS Research Paper 290, Tor Vergata University, CEIS, revised 03 Oct 2013.
    147. James Morley & Irina B. Panovska & Tara M. Sinclair, 2014. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41B, School of Economics, The University of New South Wales.
    148. Diego J. Pedregal, 2003. "Filter-Design and Model-Based Analysis of Economic Cycles," Economic Working Papers at Centro de Estudios Andaluces E2003/13, Centro de Estudios Andaluces.
    149. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Countercyclical Capital Buffers: bayesian estimates and alternatives focusing on credit growth," Working Papers Series 384, Central Bank of Brazil, Research Department.
    150. David Shepherd & Robert Dixon, 2010. "The not-so-great moderation? Evidence on changing volatility from Australian regions," Department of Economics - Working Papers Series 1090, The University of Melbourne.

  39. Jared Bernstein & Andrew Harvey, 2000. "Measurement and Testing of Inequality from Time Series of Deciles with an Application to U.S. Wages," Econometric Society World Congress 2000 Contributed Papers 0861, Econometric Society.

    Cited by:

    1. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    2. Alvaro Angeriz & Philip Arestis, 2007. "Assessing Inflation Targeting Through Intervention Analysis," Money Macro and Finance (MMF) Research Group Conference 2006 87, Money Macro and Finance Research Group.
    3. Tommaso Proietti, 2005. "Convergence in Italian regional per-capita GDP," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 497-506.
    4. Dale Belman & Paul Wolfson & Kritkorn Nawakitphaitoon, 2015. "Who Is Affected by the Minimum Wage?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 54(4), pages 582-621, October.
    5. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    6. Abraham, David & Barkai, Simcha, 2022. "Low wages aren't a growing problem," Working Papers 322, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
    7. Higson, C. & Holly, S. & Kattuman, P. & S. Platis, 2001. "The Business Cycle, Macroeconomic Shocks and the Cross Section: The Growth of UK Quoted Companies," Cambridge Working Papers in Economics 0114, Faculty of Economics, University of Cambridge.

  40. A. C. Harvey & Siem Jan Koopman, 2000. "Computing Observation Weights for Signal Extraction and Filtering," Econometric Society World Congress 2000 Contributed Papers 0888, Econometric Society.

    Cited by:

    1. Harvey, A. & Simons, J., 2024. "Hidden Threshold Models with applications to asymmetric cycles," Cambridge Working Papers in Economics 2448, Faculty of Economics, University of Cambridge.
    2. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    3. Roberta Serafini & J. Bruha & B. Pierluigi, 2011. "Euro area labour markets: different reaction to shocks?," EcoMod2011 2970, EcoMod.
    4. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.
    5. Gianfreda, Angelica & Maranzano, Paolo & Parisio, Lucia & Pelagatti, Matteo, 2023. "Testing for integration and cointegration when time series are observed with noise," Economic Modelling, Elsevier, vol. 125(C).
    6. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    7. Claudio BorioBy & Piti Disyatat & Mikael Juselius, 2017. "Rethinking potential output: embedding information about the financial cycle," Oxford Economic Papers, Oxford University Press, vol. 69(3), pages 655-677.
    8. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
    9. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-44, February.
    10. Andrés González Gómez & Lavan Mahadeva & Diego Rodríguez & Luis Eduardo Rojas, 2009. "Monetary Policy Forecasting In A Dsge Model With Data That Is Uncertain, Unbalanced And About The Future," Borradores de Economia 5480, Banco de la Republica.
    11. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    12. Danilo Leiva-Leon & Lorenzo Ductor, 2019. "Fluctuations in Global Macro Volatility," Working Papers 1925, Banco de España.
    13. 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.
    14. Fabio Busetti, 2006. "Preliminary data and econometric forecasting: an application with the Bank of Italy Quarterly Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 1-23.
    15. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    16. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    17. Mahadeva, Lavan, 2007. "Monetary Policy and Data Uncertainty: A Case Study of Distribution, Hotels and Catering Growth," Discussion Papers 19, Monetary Policy Committee Unit, Bank of England.
    18. Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
    19. Terence Mills, 2007. "A Note on Trend Decomposition: The 'Classical' Approach Revisited with an Application to Surface Temperature Trends," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(8), pages 963-972.
    20. Roberto Iannaccone & Edoardo Otranto, 2003. "Signal Extraction in Continuous Time and the Generalized Hodrick- Prescott Filter," Econometrics 0311002, University Library of Munich, Germany.
    21. Thomas Gilbert & Chiara Scotti & Georg Strasser & Clara Vega, 2015. "Is the Intrinsic Value of Macroeconomic News Announcements Related to their Asset Price Impact?," Finance and Economics Discussion Series 2015-46, Board of Governors of the Federal Reserve System (U.S.).
    22. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    23. Valentina Aprigliano & Guerino Ardizzi & Libero Monteforte, 2017. "Using the payment system data to forecast the Italian GDP," Temi di discussione (Economic working papers) 1098, Bank of Italy, Economic Research and International Relations Area.
    24. Claudio Borio & Piti Disyatat & Mikael Juselius, 2014. "A parsimonious approach to incorporating economic information in measures of potential output," BIS Working Papers 442, Bank for International Settlements.
    25. Itkonen, Juha & Juvonen, Petteri, 2017. "Nowcasting the Finnish economy with a large Bayesian vector autoregressive model," BoF Economics Review 6/2017, Bank of Finland.
    26. Elena Angelini & Marta Banbura & Gerhard Rünstler, 2010. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-22.
    27. Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2018. "Higher Frequency Hedonic Property Price Indices: A State Space Approach," Graz Economics Papers 2018-04, University of Graz, Department of Economics.
    28. Gilbert, Thomas & Scotti, Chiara & Strasser, Georg & Vega, Clara, 2017. "Is the intrinsic value of a macroeconomic news announcement related to its asset price impact?," Journal of Monetary Economics, Elsevier, vol. 92(C), pages 78-95.
    29. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    30. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    31. Maranzano, Paolo & Pelagatti, Matteo, 2024. "A Hodrick-Prescott filter with automatically selected jumps," FEEM Working Papers 344134, Fondazione Eni Enrico Mattei (FEEM).
    32. Marc Francke, 2010. "Repeat Sales Index for Thin Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 41(1), pages 24-52, July.
    33. D.S. Prasada Rao & Alicia N. Rambaldi & K. Renuka Ganegodage & L. T. Huynh & Howard E. Doran, 2017. "UQICD v2.1.2 User Guide," Discussion Papers Series 534, School of Economics, University of Queensland, Australia.
    34. Sbrana, Giacomo & Silvestrini, Andrea, 2022. "Random coefficient state-space model: Estimation and performance in M3–M4 competitions," International Journal of Forecasting, Elsevier, vol. 38(1), pages 352-366.
    35. Andrle, Michal, 2012. "Understanding DSGE Filters in Forecasting and Policy Analysis," Dynare Working Papers 16, CEPREMAP.
    36. 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.
    37. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
    38. Stéphanie Guichard & Elena Rusticelli, 2011. "A Dynamic Factor Model for World Trade Growth," OECD Economics Department Working Papers 874, OECD Publishing.
    39. Long, Wen & Zhao, Manyi & Tang, Yeran, 2021. "Can the Chinese volatility index reflect investor sentiment?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    40. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    41. Fabio Busetti, 2001. "The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model," Temi di discussione (Economic working papers) 437, Bank of Italy, Economic Research and International Relations Area.
    42. Jan Brùha, 2011. "An Empirical Small Labor Market Model for the Czech Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(5), pages 434-449, November.
    43. William R. Bell & Donald E. K. Martin, 2004. "Computation of asymmetric signal extraction filters and mean squared error for ARIMA component models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 603-623, July.
    44. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
    45. Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, vol. 181(C), pages 22-27.
    46. Chiara Scotti, 2013. "Surprise and uncertainty indexes: real-time aggregation of real-activity macro surprises," International Finance Discussion Papers 1093, Board of Governors of the Federal Reserve System (U.S.).
    47. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    48. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    49. Luis E. Rojas, 2011. "Professional Forecasters: How to Understand and Exploit Them Through a DSGE Model," Borradores de Economia 664, Banco de la Republica de Colombia.
    50. Deicy J. Cristiano-Botia & Manuel Dario Hernandez-Bejarano & Mario A. Ramos-Veloza, 2021. "Labor Market Indicator for Colombia (LMI)," Borradores de Economia 1152, Banco de la Republica de Colombia.
    51. Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
    52. Weinert, Howard L., 2007. "Efficient computation for Whittaker-Henderson smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 959-974, October.
    53. Dias, Maria Helena Ambrosio & Dias, Joilson, 2010. "Measuring the Cyclical Component of a Time Series: a New Proposed Methodology," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    54. Tommaso Proietti, 2006. "Measuring Core Inflation by Multivariate Structural Time Series Models," CEIS Research Paper 83, Tor Vergata University, CEIS.
    55. Alessandro Barbarino & Travis J. Berge & Han Chen & Andrea Stella, 2020. "Which Output Gap Estimates Are Stable in Real Time and Why?," Finance and Economics Discussion Series 2020-102, Board of Governors of the Federal Reserve System (U.S.).
    56. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    57. 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.
    58. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    59. Tóth, Máté, 2021. "A multivariate unobserved components model to estimate potential output in the euro area: a production function based approach," Working Paper Series 2523, European Central Bank.
    60. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    61. Truong, Chi & Sheen, Jeffrey & Trück, Stefan & Villafuerte, James, 2022. "Early warning systems using dynamic factor models: An application to Asian economies," Journal of Financial Stability, Elsevier, vol. 58(C).
    62. Andrew Harvey, 2010. "The local quadratic trend model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 94-108.
    63. Nicholas Sander, 2013. "Fresh perspectives on unobservable variables: Data decomposition of the Kalman smoother," Reserve Bank of New Zealand Analytical Notes series AN2013/09, Reserve Bank of New Zealand.
    64. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.
    65. Carlos Cuerpo & Ángel Cuevas & Enrique M. Quilis, 2018. "Estimating output gap: a beauty contest approach," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(3), pages 275-304, August.
    66. Alicia N. Rambaldi & Cameron S. Fletcher, 2014. "Hedonic Imputed Property Price Indexes: The Effects of Econometric Modeling Choices," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 423-448, November.

  41. Nyblom, Jukka & Harvey, Andrew, 1999. "Tests of Common Stochastic Trends," Cambridge Working Papers in Economics 9902, Faculty of Economics, University of Cambridge.

    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. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," Stirling Economics Discussion Papers 2014-12, University of Stirling, Division of Economics.
    3. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    4. Nyblom, Jukka, 2001. "Invariant Tests for Covariance Structures in Multivariate Linear Model," Journal of Multivariate Analysis, Elsevier, vol. 76(2), pages 294-315, February.
    5. 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.
    6. Yicong Lin & Hanno Reuvers, 2019. "Efficient Estimation by Fully Modified GLS with an Application to the Environmental Kuznets Curve," Papers 1908.02552, arXiv.org, revised Aug 2020.
    7. Won-Ki Seo, 2020. "Functional Principal Component Analysis for Cointegrated Functional Time Series," Papers 2011.12781, arXiv.org, revised Apr 2023.
    8. Sven Schreiber, 2012. "Estimating the natural rate of unemployment in euro-area countries with co-integrated systems," Applied Economics, Taylor & Francis Journals, vol. 44(10), pages 1315-1335, April.
    9. Arvid Raknerud, 2001. "A State Space Approach for Estimating VAR Models for Panel Data with Latent Dynamic Components," Discussion Papers 295, Statistics Norway, Research Department.
    10. Jen-Je Su, 2003. "On the power of the multivariate KPSS test of stationarity against fractionally integrated alternatives," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 637-641.
    11. Aizenman, Joshua & Pasricha, Gurnain Kaur, 2010. "Selective swap arrangements and the global financial crisis: Analysis and interpretation," International Review of Economics & Finance, Elsevier, vol. 19(3), pages 353-365, June.
    12. Josep Lluís Carrion‐i‐Silvestre & Andreu Sansó, 2006. "Testing the Null of Cointegration with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(5), pages 623-646, October.
    13. 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.
    14. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2014. "Unemployment Rate Hysteresis and the Great Recession: Exploring the Metropolitan Evidence," Working Papers 1403, University of Nevada, Las Vegas , Department of Economics.
    15. Bruno, Giancarlo & Malgarini, Marco, 2002. "An Indicator of Economic Sentiment for the Italian Economy," MPRA Paper 42331, University Library of Munich, Germany.
    16. Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.
    17. Aizenman, Joshua & Jinjarak, Yothin, 2009. "Current account patterns and national real estate markets," Journal of Urban Economics, Elsevier, vol. 66(2), pages 75-89, September.
    18. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    19. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
    20. Tucker McElroy & Michael W. McCracken, 2017. "Multistep ahead forecasting of vector time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 495-513, May.
    21. Pelagatti, Matteo M. & Sen, Pranab K., 2013. "Rank tests for short memory stationarity," Journal of Econometrics, Elsevier, vol. 172(1), pages 90-105.
    22. Di Casola, Paola & Sichlimiris, Spyridon, 2020. "TFP news, stock market booms and the business cycle: Revisiting the evidence with VEC models," Working Paper Series 388, Sveriges Riksbank (Central Bank of Sweden).
    23. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    24. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    25. Müller, Ulrich K. & Watson, Mark W., 2013. "Low-frequency robust cointegration testing," Journal of Econometrics, Elsevier, vol. 174(2), pages 66-81.
    26. Shahriyar Mukhtarov & Jeyhun I. Mikayilov & Sugra Humbatova & Vugar Muradov, 2020. "Do High Oil Prices Obstruct the Transition to Renewable Energy Consumption?," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    27. Morten {O}rregaard Nielsen & Won-Ki Seo & Dakyung Seong, 2023. "Inference on common trends in functional time series," Papers 2312.00590, arXiv.org, revised May 2024.
    28. Al-Sadoon, Majid M., 2017. "A unifying theory of tests of rank," Journal of Econometrics, Elsevier, vol. 199(1), pages 49-62.
    29. Shahriyar Mukhtarov & Sugra Humbatova & Natig Gadim-Oglu Hajiyev, 2021. "Is the Transition to Renewable Energy Consumption Hampered by High Oil Prices?," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 377-380.
    30. I. A. Moosa & J. L. Baxter, 2002. "Modelling the trend and seasonals within an AIDS model of the demand for alcoholic beverages in the United Kingdom," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 95-106.
    31. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    32. MAGAZZINO, Cosimo & LEOGRANDE, Angelo, 2021. "Subjective Well-Being In Italian Regions: A Panel Data Approach," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 21(1), pages 1-18.
    33. 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.
    34. John T. Barkoulas & Christopher F. Baum & Atreya Chakraborty, 2000. "Forward Premiums and Market Efficiency: Panel Unit-root Evidence from the Term Structure of Forward Premiums," Boston College Working Papers in Economics 461, Boston College Department of Economics, revised 13 Jun 2001.
    35. James Morley & Tara M. Sinclair, 2005. "Testing for Stationarity and Cointegration in an Unobserved Components Framework," Computing in Economics and Finance 2005 451, Society for Computational Economics.
    36. Auci, Sabrina & Becchetti, Leonardo, 2006. "The instability of the adjusted and unadjusted environmental Kuznets curves," Ecological Economics, Elsevier, vol. 60(1), pages 282-298, November.
    37. Qihui Chen & Zheng Fang, 2018. "Improved Inference on the Rank of a Matrix," Papers 1812.02337, arXiv.org, revised Mar 2019.
    38. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2020. "Are unemployment rates in OECD countries stationary? Evidence from univariate and panel unit root tests," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    39. Ricardo Batista Politi & Enlinson Mattos, 2011. "Ad-valorem tax incidence and after-tax price adjustments: evidence from Brazilian basic basket food," Canadian Journal of Economics, Canadian Economics Association, vol. 44(4), pages 1438-1470, November.
    40. Tommaso Proietti, 2005. "Convergence in Italian regional per-capita GDP," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 497-506.
    41. Zanetti Chini, Emilio, 2010. "Does the purchasing power parity hypothesis hold after 1998?," MPRA Paper 27225, University Library of Munich, Germany.
    42. 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.
    43. 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.
    44. Riccardo Corradini, 2005. "An Empirical Analysis of Permanent Income Hypothesis Applied to Italy using State Space Models with non zero correlation between trend and cycle," Econometrics 0509009, University Library of Munich, Germany.
    45. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.
    46. Avalos, Roger & Fitzgerald, Timothy & Rucker, Randal R., 2016. "Measuring the effects of natural gas pipeline constraints on regional pricing and market integration," Energy Economics, Elsevier, vol. 60(C), pages 217-231.
    47. Morten Ørregaard Nielsen, 2005. "Multivariate Lagrange Multiplier Tests for Fractional Integration," Journal of Financial Econometrics, Oxford University Press, vol. 3(3), pages 372-398.
    48. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2001. "Unité et pluralité du cycle européen," Post-Print hal-03458556, HAL.
    49. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    50. Søren Johansen, 2014. "Times Series: Cointegration," CREATES Research Papers 2014-38, Department of Economics and Business Economics, Aarhus University.
    51. Apergis, Nicholas & Fafaliou, Irene & Stefanitsis, Marinos, 2016. "Asymmetric information and employment: evidence from the U.S. banking sector," The Journal of Economic Asymmetries, Elsevier, vol. 14(PB), pages 199-210.
    52. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    53. Harvey, A. & Vasco Carvalho, 2002. "Models for Converging Economies," Cambridge Working Papers in Economics 0216, Faculty of Economics, University of Cambridge.
    54. Nicholas Apergis & Beatrice D. Simo-Kengne & Rangan Gupta & Tsangyao Chang, 2013. "The Dynamic Relationship between House Prices and Output: Evidence from US Metropolitan Statistical Areas," Working Papers 201349, University of Pretoria, Department of Economics.
    55. 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.
    56. Kongsted, Hans Christian, 2005. "Testing the nominal-to-real transformation," Journal of Econometrics, Elsevier, vol. 124(2), pages 205-225, February.
    57. Chen, Xiaoshan & MacDonald, Ronald, 2010. "Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models," SIRE Discussion Papers 2010-41, Scottish Institute for Research in Economics (SIRE).
    58. Haldrup, Niels, "undated". "Empirical analysis of price data in the delineation of the relevant geographical market in competition analysis," Economics Working Papers 2003-9, Department of Economics and Business Economics, Aarhus University.
    59. Fabio Busetti, 2012. "On detecting end-of-sample instabilities," Temi di discussione (Economic working papers) 881, Bank of Italy, Economic Research and International Relations Area.
    60. Auld, T., 2022. "Betting and financial markets are cointegrated on election night," Cambridge Working Papers in Economics 2263, Faculty of Economics, University of Cambridge.
    61. Esa Mangeloja, 2003. "Structural testing of Business Cycles," Macroeconomics 0308004, University Library of Munich, Germany.
    62. Tucker McElroy & Thomas Trimbur, 2015. "Signal Extraction for Non-Stationary Multivariate Time Series with Illustrations for Trend Inflation," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 209-227, March.
    63. Brüggemann, Ralf, 2001. "Sources of German unemployment: A structural vector error correction analysis," SFB 373 Discussion Papers 2001,19, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    64. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.
    65. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    66. Jansson, Michael, 2004. "Stationarity Testing With Covariates," Econometric Theory, Cambridge University Press, vol. 20(1), pages 56-94, February.
    67. Baigorri, Carlos M. & Maldonado, Wilfredo F.L., 2014. "Optimal mobile termination rate: The Brazilian mobile market case," Telecommunications Policy, Elsevier, vol. 38(1), pages 86-95.
    68. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    69. Lorenzo Lucchese & Mikko Pakkanen & Almut Veraart, 2022. "The Short-Term Predictability of Returns in Order Book Markets: a Deep Learning Perspective," Papers 2211.13777, arXiv.org, revised Oct 2023.
    70. Guglielmo Maria Caporale & Marinko Skare, 2011. "Employment Growth, Inflation and Output Growth: Was Phillips Right?: Evidence from a Dynamic Panel," Discussion Papers of DIW Berlin 1138, DIW Berlin, German Institute for Economic Research.
    71. Jönsson, Kristian, 2004. "Testing for Stationarity in Panel Data Models when Disturbances are Cross-Sectionally Correlated," Working Papers 2004:17, Lund University, Department of Economics, revised 26 Nov 2004.
    72. 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.
    73. 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.
    74. Majid M. Al-Sadoon, 2014. "A general theory of rank testing," Economics Working Papers 1411, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2015.
    75. Rath, Deba Prasad & Misra, Biswa Swarup, 2006. "Examining Sustainability of Federal Finances in India: An Application of Non-stationary Panel Methods," MPRA Paper 21894, University Library of Munich, Germany.
    76. Tucker S McElroy & Agnieszka Jach, 2019. "Testing collinearity of vector time series," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 97-116.
    77. Mikayilov, Jeyhun I. & Darandary, Abdulelah & Alyamani, Ryan & Hasanov, Fakhri J. & Alatawi, Hatem, 2020. "Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand," Energy Policy, Elsevier, vol. 146(C).
    78. Hans Christian Kongsted, 2002. "Testing the Nominal-to-Real Transformation," Discussion Papers 02-06, University of Copenhagen. Department of Economics.
    79. Choi, Chi-Young, 2004. "Searching for evidence of long-run PPP from a post-Bretton Woods panel: separating the wheat from the chaff," Journal of International Money and Finance, Elsevier, vol. 23(7-8), pages 1159-1186.
    80. Javier Gómez Biscarri & Javier Hualde, 2014. "Regression-based analysis of cointegration systems," Working Papers 780, Barcelona School of Economics.
    81. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.
    82. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.

  42. Harvey, A.C. & Koopman, S.J.M., 1999. "Signal Extraction and the Formulation of Unobserved Components Models," Discussion Paper 1999-44, Tilburg University, Center for Economic Research.

    Cited by:

    1. Ralph D Snyder, 2005. "A Pedant's Approach to Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 5/05, Monash University, Department of Econometrics and Business Statistics.
    2. Sbrana, Giacomo & Silvestrini, Andrea, 2020. "Forecasting with the damped trend model using the structural approach," International Journal of Production Economics, Elsevier, vol. 226(C).
    3. Tommaso Proietti, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Econometrics 0209002, University Library of Munich, Germany.
    4. Chen, Yen-Hsiao & Quan, Lianfeng & Liu, Yang, 2013. "An empirical investigation on the temporal properties of China's GDP," China Economic Review, Elsevier, vol. 27(C), pages 69-81.
    5. Kum Hwa Oh & Eric Zivot & Drew Creal, 2006. "The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks," Working Papers UWEC-2006-16-FC, University of Washington, Department of Economics.
    6. Chin Nam Low & Heather Anderson & Ralph Snyder, 2006. "Beverridge Nelson Decomposition With Markov Switching," CAMA Working Papers 2006-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Heather M. Anderson & Chin Nam Low & Ralph Snyder, 2004. "Single Source of Error State Space Approach to the Beveridge Nelson Decomposition," Monash Econometrics and Business Statistics Working Papers 21/04, Monash University, Department of Econometrics and Business Statistics.
    8. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    9. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.
    10. A. Peyrache & A. N. Rambaldi, 2017. "Incorporating temporal and country heterogeneity in growth accounting—an application to EU-KLEMS," Journal of Productivity Analysis, Springer, vol. 47(2), pages 143-166, April.
    11. Cain, P.M., 2022. "Modelling short-and long-term marketing effects in the consumer purchase journey," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 96-116.
    12. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    13. Thomas B. King, 2005. "Labor productivity and job-market flows: trends, cycles, and correlations," Supervisory Policy Analysis Working Papers 2005-04, Federal Reserve Bank of St. Louis.
    14. Breitung, Jorg & Hafner, Christian, 2016. "A simple model for now-casting volatility series," LIDAM Reprints ISBA 2016040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
    16. Koop, Gary M & Tobias, Justin, 2006. "Semiparametric Bayesian Inference in Smooth Coefficient Models," Staff General Research Papers Archive 12202, Iowa State University, Department of Economics.
    17. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    18. A. C. Harvey & Siem Jan Koopman, 2000. "Computing Observation Weights for Signal Extraction and Filtering," Econometric Society World Congress 2000 Contributed Papers 0888, Econometric Society.
    19. Rob J Hyndman & Maxwell L. King & Ivet Pitrun & Baki Billah, 2002. "Local Linear Forecasts Using Cubic Smoothing Splines," Monash Econometrics and Business Statistics Working Papers 10/02, Monash University, Department of Econometrics and Business Statistics.
    20. J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
    21. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    22. 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.
    23. B. Jungbacker & S.J. Koopman, 2005. "Model-based Measurement of Actual Volatility in High-Frequency Data," Tinbergen Institute Discussion Papers 05-002/4, Tinbergen Institute.
    24. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.
    25. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    26. Marc Francke, 2010. "Repeat Sales Index for Thin Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 41(1), pages 24-52, July.
    27. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
    28. 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.
    29. Victor M. Guerrero, 2008. "Estimating Trends with Percentage of Smoothness Chosen by the User," International Statistical Review, International Statistical Institute, vol. 76(2), pages 187-202, August.
    30. Paul Alagidede, 2012. "Trends And Cycles In The Net Barter Terms Of Trade For Sub-Saharan Africa's Primary Commodity Exporters," Journal of Developing Areas, Tennessee State University, College of Business, vol. 46(2), pages 213-229, July-Dece.
    31. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    32. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
    33. Guisinger, Amy Y. & Owyang, Michael T. & Soques, Daniel, 2024. "Industrial Connectedness and Business Cycle Comovements," Econometrics and Statistics, Elsevier, vol. 29(C), pages 132-149.
    34. Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
    35. Philip Kostov & John Lingard, 2004. "Recurrence analysis techniques for non-stationary and non-linear data," Microeconomics 0409003, University Library of Munich, Germany.
    36. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    37. Tommaso Proietti, 2006. "Measuring Core Inflation by Multivariate Structural Time Series Models," CEIS Research Paper 83, Tor Vergata University, CEIS.
    38. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    39. Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
    40. Tommaso Proietti, 2007. "Band Spectral Estimation for Signal Extraction," CEIS Research Paper 104, Tor Vergata University, CEIS.
    41. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    42. Ralph D. Snyder, 2004. "Exponential Smoothing: A Prediction Error Decomposition Principle," Monash Econometrics and Business Statistics Working Papers 15/04, Monash University, Department of Econometrics and Business Statistics.
    43. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    44. Mardi Dungey & Jan P. A. M. Jacobs & Jing Tian & Simon van Norden, 2013. "Trend-cycle decomposition: implications from an exact structural identification," Working Papers 13-22, Federal Reserve Bank of Philadelphia.
    45. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    46. Borus Jungbacker & Siem Jan Koopman, 2006. "Model-Based Measurement of Actual Volatility in High-Frequency Data," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 183-210, Emerald Group Publishing Limited.

  43. Busetti, Fabio & Harvey, Andrew, 1998. "Testing for the presence of a random walk in series with structural breaks," LSE Research Online Documents on Economics 6870, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    2. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
    3. Tommaso Proietti & Alberto Musso, 2012. "Growth accounting for the euro area," Empirical Economics, Springer, vol. 43(1), pages 219-244, August.
    4. Muhammad Zeeshan Younas & Rashid Mehmood, 2018. "Examining the Efficiency of American Stock Exchange NASDAQ: An empirical analysis of the Market Efficiency Hypothesis," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 7(3), pages 132-137, September.
    5. Carrion-i-Silvestre, Josep Lluis, 2003. "Breaking date misspecification error for the level shift KPSS test," Economics Letters, Elsevier, vol. 81(3), pages 365-371, December.
    6. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Working Papers 0043, Gaidar Institute for Economic Policy, revised 2013.
    7. Su, Chi-Wei & Tsangyao, Chang & Chang, Hsu-Ling, 2011. "Purchasing power parity for fifteen Latin American countries: Stationary test with a Fourier function," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 839-845, October.
    8. Yoichi Arai & Eiji Kurozumi, 2007. "Testing for the Null Hypothesis of Cointegration with a Structural Break," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 705-739.
    9. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    10. Giuseppe Cavaliere & A. M. Robert Taylor, 2006. "Testing for a change in persistence in the presence of non-stationary volatility," Discussion Papers 06/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    11. Fabio Busetti & Andrew Harvey, 2003. "Further Comments On Stationarity Tests In Series With Structural Breaks At Unknown Points," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 137-140, March.
    12. Jerome Geyer‐Klingeberg & Andreas W. Rathgeber, 2021. "Determinants of the WTI‐Brent price spread revisited," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 736-757, May.
    13. Francisco Delgado & Maria Jose Presno, 2011. "Convergence of fiscal pressure in the EU: a time series approach," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4257-4267.
    14. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion - in Russian," Working Papers 0044, Gaidar Institute for Economic Policy, revised 2012.
    15. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    16. 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.
    17. David I. Harvey & Terence C. Mills, 2003. "A Note On Busetti–Harvey Tests For Stationarity In Series With Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 159-164, March.
    18. Joakim Westerlund & David L. Edgerton, 2007. "New Improved Tests for Cointegration with Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(2), pages 188-224, March.
    19. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    20. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2005. "Stationarity Tests Under Time-Varying Second Moments," Econometric Theory, Cambridge University Press, vol. 21(6), pages 1112-1129, December.
    21. 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.
    22. 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.
    23. Kaddour Hadri & Rolf Larsson & Yao Rao, 2012. "Testing For Stationarity With A Break In Panels Where The Time Dimension Is Finite," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 123-148, December.
    24. Emilian DOBRESCU, 2016. "Controversies over the Size of the Public Budget," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-34, December.
    25. Harvey, A. & Thiele, S., 2017. "Co-integration and control: assessing the impact of events using time series data," Cambridge Working Papers in Economics 1731, Faculty of Economics, University of Cambridge.
    26. Josep Carrion-i-Silvestre & Andreu Sansó, 2007. "The KPSS test with two structural breaks," Spanish Economic Review, Springer;Spanish Economic Association, vol. 9(2), pages 105-127, June.
    27. Kaddour Hadri & Yao Rao, 2008. "Panel Stationarity Test with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 245-269, April.
    28. A. M. Robert Taylor, 2005. "Fluctuation Tests for a Change in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 207-230, April.
    29. David I. Harvey & Terence C. Mills, 2004. "Tests for Stationarity in Series with Endogenously Determined Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 863-894, December.
    30. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    31. Karsten Schweikert, 2019. "Asymmetric price transmission in the US and German fuel markets: a quantile autoregression approach," Empirical Economics, Springer, vol. 56(3), pages 1071-1095, March.
    32. Corona, Francisco & Orraca, Pedro, 2016. "Remittances in Mexico and their unobserved components," DES - Working Papers. Statistics and Econometrics. WS 22674, Universidad Carlos III de Madrid. Departamento de Estadística.
    33. Dimpfl, Thomas & Peter, Franziska J., 2019. "Group transfer entropy with an application to cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 543-551.
    34. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    35. María Presno & Manuel Landajo, 2010. "Computation of limiting distributions in stationarity testing with a generic trend," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(2), pages 165-183, March.
    36. 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.
    37. 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.
    38. Iacone, Fabrizio & Leybourne, Stephen J. & Robert Taylor, A.M., 2013. "Testing for a break in trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 176(1), pages 30-45.
    39. Tommaso PROIETTI & Alberto MUSSO & Thomas WESTERMANN, 2002. "Estimating Potential Output and the Output Gap for the Euro Area: a Model-Based Production Function Approach," Economics Working Papers ECO2002/09, European University Institute.
    40. Josep Lluís Carrion‐i‐Silvestre & María Dolores Gadea, 2023. "Testing for multiple level shifts with an integrated or stationary noise component," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 801-819, September.
    41. Josep Lluis Carrion Silvestre & Tomas del Barrio Castro & Enrique Lopez Bazo, 2003. "Breaking the panels. An application to the GDP per capita," Working Papers in Economics 97, Universitat de Barcelona. Espai de Recerca en Economia.
    42. Yoichi Arai & Eiji Kurozumi, 2005. "Testing for the Null Hypothesis of Cointegration with Structural Breaks (Subsequently published in "Econometric Reviews", Volume 26, Issue 6 November 2007, pages 705 - 739. )," CARF F-Series CARF-F-022, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    43. 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.
    44. María Presno & Anna López, 2003. "Testing for stationarity in series with a shift in the mean. A fredholm approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 195-213, June.
    45. Musso, Alberto & Proietti, Tommaso, 2007. "Growth accounting for the euro area: a structural approach," Working Paper Series 804, European Central Bank.

  44. Andrew C Harvey & Siem Jan Koopman, 1996. "Multivariate Structural Time Series Models - (Now published in 'System Dynamics in Economic and Financial Models', CHeij, H Schumacher, B Hanzon and C Praagman (eds.) John Wiley & Sons, Chichester (19," STICERD - Econometrics Paper Series 307, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2002. "Unity and Plurality of the European Cycle," Documents de Travail de l'OFCE 2002-03, Observatoire Francais des Conjonctures Economiques (OFCE).

  45. Eric Ghysels & Andrew Harvey & Eric Renault, 1995. "Stochastic Volatility," CIRANO Working Papers 95s-49, CIRANO.

    Cited by:

    1. Per Frederiksen & Morten Orregaard Nielsen, 2008. "Bias-Reduced Estimation of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 496-512, Fall.
    2. Takaishi, Tetsuya, 2018. "Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 139-154.
    3. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    4. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    5. Bengt Holmström & Jean Tirole, 2001. "LAPM: A Liquidity‐Based Asset Pricing Model," Journal of Finance, American Finance Association, vol. 56(5), pages 1837-1867, October.
    6. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Econometrics of testing for jumps in financial economics using bipower variation," Economics Papers 2003-W21, Economics Group, Nuffield College, University of Oxford.
    7. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    8. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques.
    9. VEREDAS, David & RODRIGUEZ-POO, Juan & ESPASA, Antoni, 2002. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," LIDAM Discussion Papers CORE 2002023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Ghysels, Eric & Guay, Alain, 2003. "Structural change tests for simulated method of moments," Journal of Econometrics, Elsevier, vol. 115(1), pages 91-123, July.
    11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    12. Belton Fleisher & Dongwei Su, 1998. "Why Does Return Volatility Differ in Chinese Stock Markets?," Working Papers 98-03, Ohio State University, Department of Economics.
    13. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    14. Peter Bossaert & Eric Ghysels & Christian Gouriéroux, 1996. "Arbitrage Based Pricing When Volatility Is Stochastic," CIRANO Working Papers 96s-20, CIRANO.
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    295. Durham, Garland B., 2003. "Likelihood-based specification analysis of continuous-time models of the short-term interest rate," Journal of Financial Economics, Elsevier, vol. 70(3), pages 463-487, December.
    296. Thomakos, Dimitrios D. & Wang, Tao & Wille, Luc T., 2002. "Modeling daily realized futures volatility with singular spectrum analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 505-519.
    297. Chacko, George & Viceira, Luis M., 2003. "Spectral GMM estimation of continuous-time processes," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 259-292.

  46. Andrew C Harvey & Andrew Scott, 1994. "Seasonality in Dynamic Regression Models," CEP Discussion Papers dp0184, Centre for Economic Performance, LSE.

    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. 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. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    4. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters, in: Lester C. Hunt (ed.), Energy in a Competitive Market, chapter 9, Edward Elgar Publishing.
    5. Ramsay, James O. & Ramsey, James B., 2002. "Functional data analysis of the dynamics of the monthly index of nondurable goods production," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 327-344, March.
    6. Stephen Bazen & Vêlayoudom Marimoutou, 2018. "Federal Minimum Wage Hikes Do Reduce Teenage Employment," AMSE Working Papers 1850, Aix-Marseille School of Economics, France.
    7. Murali Adhikari & Krishna Paudel & Laxmi Paudel & James Bukenya, 2007. "Modelling swine supply response using a structural time series approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(7), pages 467-472.
    8. Bernardina Algieri, 2011. "Modelling export equations using an unobserved component model: the case of the Euro Area and its competitors," Empirical Economics, Springer, vol. 41(3), pages 593-637, December.
    9. Moosa, Imad A., 1999. "Cyclical output, cyclical unemployment, and Okun's coefficient A structural time series approach," International Review of Economics & Finance, Elsevier, vol. 8(3), pages 293-304, September.
    10. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    11. Khalid Al-Saad & Imad Moosa, 2005. "Seasonality in stock returns: evidence from an emerging market," Applied Financial Economics, Taylor & Francis Journals, vol. 15(1), pages 63-71.
    12. Dadashova, Bahar & Ramírez Arenas, Blanca & McWilliams Mira, José & Izquierdo Aparicio, Francisco, 2014. "Explanatory and prediction power of two macro models. An application to van-involved accidents in Spain," Transport Policy, Elsevier, vol. 32(C), pages 203-217.
    13. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    14. James Rude & Yves Surry, 2014. "Canadian Hog Supply Response: A Provincial Level Analysis," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 62(2), pages 149-169, June.
    15. Alan Carruth & Andrew Dickerson, 2003. "An asymmetric error correction model of UK consumer spending," Applied Economics, Taylor & Francis Journals, vol. 35(6), pages 619-630.
    16. Zafer Dilaver & Lester C Hunt, 2010. "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 129, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    17. Moosa, Imad A. & Choe, Chongwoo, 1998. "Is the Korean economy export-driven?," Economic Modelling, Elsevier, vol. 15(2), pages 237-255, April.
    18. Haiyan Song & Peter Romilly & Xiaming Liu, 1998. "The UK consumption function and structural instability: improving forecasting performance using a time-varying parameter approach," Applied Economics, Taylor & Francis Journals, vol. 30(7), pages 975-983.
    19. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    20. Jonathan Aylen & Kevin Albertson & Gina Cavan, 2014. "The impact of weather and climate on tourist demand: the case of Chester Zoo," Climatic Change, Springer, vol. 127(2), pages 183-197, November.
    21. 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.
    22. Harry M. Karamujic, 2011. "Comparative Analysis of Australian Residential Mortgage (Home Loan) Interest Rates," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 5(3), pages 311-341, August.
    23. Joao Tovar Jalles, 2009. "Structural time series models and the Kalman filter: a concise review," Nova SBE Working Paper Series wp541, Universidade Nova de Lisboa, Nova School of Business and Economics.
    24. Mark Hon & Soo-Keong Yong, 2004. "The price of owning a car: an analysis of auction quota premium in Singapore," Applied Economics, Taylor & Francis Journals, vol. 36(7), pages 739-751.
    25. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    26. Zafer Dilaver & Lester C Hunt, 2010. "Modelling and Forecasting Turkish Residential Electricity Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 131, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    27. Abdullah Al-Awadhi & Ahmad Bash & Fouad Jamaani, 2021. "Ramadan Effect: A Structural Time-Series Test," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(1), pages 260-269, January.
    28. Hylleberg, S. & Pagan, A. R., 1997. "Seasonal integration and the evolving seasonals model," International Journal of Forecasting, Elsevier, vol. 13(3), pages 329-340, September.
    29. Petr Kadeřábek, 2007. "Jednoduchý model interakce CPI a PPI: aplikace na měsíční data zemí EU [A Simple Model of Interaction Between CPI and PPI: Application to Monthly Data of EU Countries]," Politická ekonomie, Prague University of Economics and Business, vol. 2007(2), pages 226-244.
    30. António Afonso & João Tovar Jalles, 2011. "A Longer-run Perspective on Fiscal Sustainability," Working Papers Department of Economics 2011/17, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    31. 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.
    32. Girardin, Eric & Liu, Zhenya, 2005. "Bank credit and seasonal anomalies in China's stock markets," China Economic Review, Elsevier, vol. 16(4), pages 465-483.
    33. Paramsothy Silvapulle & Imad A. Moosa & Mervyn J. Silvapulle, 2004. "Asymmetry in Okun's law," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 37(2), pages 353-374, May.
    34. F. Butter & S. Koopman, 2001. "Interaction between structural and cyclical shocks in production and employment," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 137(2), pages 273-296, June.
    35. Martyn Duffy, 2006. "Tobacco consumption and policy in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1235-1257.
    36. Stephen Bazen & Velayoudom Marimoutou, 2000. "Looking for a Needle in a Haystack? A Structural Time Series Model of the Relationship Between Teenage Employment and Minimum Wages in the United States," Econometric Society World Congress 2000 Contributed Papers 0495, Econometric Society.
    37. Koenig, P., 2012. "The effect of LNG on the rleationship between UK and Continental European natural gas markets," Cambridge Working Papers in Economics 1253, Faculty of Economics, University of Cambridge.
    38. Talla Al-Deehani, 2006. "Seasonality as an unobservable component: the case of Kuwait stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(6), pages 471-478.
    39. Liam Lenten & Imad Moosa, 1999. "Modelling the trend and seasonality in the consumption of alcoholic beverages in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 31(7), pages 795-804.
    40. Jamel Gatfaoui & Eric Girardin, 2015. "Comovement of Chinese provincial business cycles," Post-Print hal-01456105, HAL.
    41. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    42. Hansen, Hermann-Josef, 1996. "Der Einfluß der Zinsen auf den privaten Verbrauch in Deutschland," Discussion Paper Series 1: Economic Studies 1996,03, Deutsche Bundesbank.
    43. Hansen, Hermann-Josef, 1996. "The impact of interest rates on private consumption in Germany," Discussion Paper Series 1: Economic Studies 1996,03e, Deutsche Bundesbank.
    44. Taylor, A. M. Robert, 1997. "On the practical problems of computing seasonal unit root tests," International Journal of Forecasting, Elsevier, vol. 13(3), pages 307-318, September.
    45. Enrique M. Quilis(1), "undated". "Modelos Bvar: Especificación, Estimación E Inferencia," Working Papers 8-02 Classification-JEL :, Instituto de Estudios Fiscales.
    46. Stephen Bazen & Velayoudom Marimoutou, 2002. "Looking for a Needle in a Haystack? A Re‐examination of the Time Series Relationship between Teenage Employment and Minimum Wages in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(supplemen), pages 699-725, December.
    47. Sulaiman T. Al-Abduljader, 2019. "Interdependence of Securitized Real Estate in Frontier Markets," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 83-108.
    48. Murali Adhikari & Krishna Paudel & Jack Houstan & James Bukenya, 2007. "Dairy supply response under stochastic trend and seasonality," Applied Economics Letters, Taylor & Francis Journals, vol. 14(12), pages 887-891.
    49. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.

  47. Andrew C Harvey & N.G. Shephard, 1993. "Estimation and Testing of Stochastic Variance Models," STICERD - Econometrics Paper Series 268, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques.
    2. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    3. Hwang, Soosung & Satchell, Stephen E., 2000. "Market risk and the concept of fundamental volatility: Measuring volatility across asset and derivative markets and testing for the impact of derivatives markets on financial markets," Journal of Banking & Finance, Elsevier, vol. 24(5), pages 759-785, May.
    4. Francis E. Warnock & Veronica C. Warnock, 2000. "The declining volatility of U.S. employment: was Arthur Burns right?," International Finance Discussion Papers 677, Board of Governors of the Federal Reserve System (U.S.).
    5. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    6. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    7. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    8. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Francis X. Diebold & Jose A. Lopez, 1995. "Measuring Volatility Dynamics," NBER Technical Working Papers 0173, National Bureau of Economic Research, Inc.
    10. P. Girardello & Orietta Nicolis & Giovanni Tondini, 2002. "Comparing conditional variance models: Theory and empirical evidence," Departmental Working Papers 2002-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    11. Alin Sima, 2008. "Stylized Facts and Discrete Stochastic Volatility Models," Advances in Economic and Financial Research - DOFIN Working Paper Series 10, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    12. Ramaprasad Bhar, 2010. "Stochastic Filtering with Applications in Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736, December.
    13. Alejandro Islas Camargo & Francisco Venegas Martínez, 2003. "Pricing Derivatives Securities with Prior Information on Long- Memory Volatility," Economía Mexicana NUEVA ÉPOCA, CIDE, División de Economía, vol. 0(1), pages 103-134, January-J.
    14. Ronald Mahieu & Peter C. Schotman, 1994. "Stochastic volatility and the distribution of exchange rate news," Discussion Paper / Institute for Empirical Macroeconomics 96, Federal Reserve Bank of Minneapolis.
    15. G Sandmann & Siem Jan Koopman, 1996. "Maximum Likelihood Estimation of Stochastic Volatility Models," FMG Discussion Papers dp248, Financial Markets Group.
    16. J. I. Pena & E. Ruiz, 1995. "Stock market regulations and international financial integration: the case of Spain," The European Journal of Finance, Taylor & Francis Journals, vol. 1(4), pages 367-382.
    17. Ramaprasad Bhar & Damien Lee, 2018. "Alternative characterization of volatility of short-term interest rate," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-15, June.
    18. Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
    19. Soosung Hwang & Steve E. Satchell & Pedro L. Valls Pereira, 2004. "How Persistent is Volatility? An Answer with Stochastic Volatility Models with Markov Regime Switching State Equations," Econometric Society 2004 Latin American Meetings 198, Econometric Society.
    20. Bjorn Hansson & Peter Hordahl, 2005. "Forecasting variance using stochastic volatility and GARCH," The European Journal of Finance, Taylor & Francis Journals, vol. 11(1), pages 33-57.
    21. Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.
    22. Mike So & K. Lam & W. K. Li, 1999. "Forecasting exchange rate volatility using autoregressive random variance model," Applied Financial Economics, Taylor & Francis Journals, vol. 9(6), pages 583-591.
    23. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    24. Ester Ruiz & Fernando Lorenzo, 1998. "The relation between the level and uncertainty of inflation," Documentos de Trabajo (working papers) 0698, Department of Economics - dECON.

Articles

  1. Harvey, Andrew & Palumbo, Dario, 2023. "Score-driven models for realized volatility," Journal of Econometrics, Elsevier, vol. 237(2).
    See citations under working paper version above.
  2. Andrew Harvey & Stephen Thiele, 2021. "Cointegration and control: Assessing the impact of events using time series data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 71-85, January.
    See citations under working paper version above.
  3. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.

    Cited by:

    1. Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    2. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    4. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    5. De Rossi, Giuliano & Steliaros, Michael, 2022. "The Shift from Active to Passive and its Effect on Intraday Stock Dynamics," Journal of Banking & Finance, Elsevier, vol. 143(C).
    6. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," 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. 29(3), pages 859-874, September.
    7. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    8. Song, Shijia & Li, Handong, 2023. "A method for predicting VaR by aggregating generalized distributions driven by the dynamic conditional score," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 203-214.

  4. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.

    Cited by:

    1. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    2. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    3. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    4. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    5. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    6. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    7. Elisa Navarra, 2022. "Stock Market Response to Firms’ Misconduct," Working Papers ECARES 2022-40, ULB -- Universite Libre de Bruxelles.
    8. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    9. Ciarreta, Aitor & Pizarro-Irizar, Cristina & Zarraga, Ainhoa, 2020. "Renewable energy regulation and structural breaks: An empirical analysis of Spanish electricity price volatility," Energy Economics, Elsevier, vol. 88(C).
    10. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    11. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    12. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.
    13. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yu, Keming, 2020. "Mixed data sampling expectile regression with applications to measuring financial risk," Economic Modelling, Elsevier, vol. 91(C), pages 469-486.

  5. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    See citations under working paper version above.
  6. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    See citations under working paper version above.
  7. Michele Caivano & Andrew Harvey & Alessandra Luati, 2016. "Robust time series models with trend and seasonal components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 99-120, March.

    Cited by:

    1. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    3. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    4. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    6. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    7. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    8. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    9. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    10. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
    12. Sarlo, Rodrigo & Fernandes, Cristiano & Borenstein, Denis, 2023. "Lumpy and intermittent retail demand forecasts with score-driven models," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1146-1160.

  8. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    See citations under working paper version above.
  9. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    See citations under working paper version above.
  10. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    See citations under working paper version above.
  11. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.

    Cited by:

    1. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Papers 2305.13123, arXiv.org.
    2. Yan, Hanhuan & Han, Liyan, 2019. "Empirical distributions of stock returns: Mixed normal or kernel density?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 473-486.
    3. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    4. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    5. Marcin Dec, 2021. "From point through density valuation to individual risk assessment in the discounted cash flows method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5621-5635, October.
    6. Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    7. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    8. Matthieu Garcin & Jules Klein & Sana Laaribi, 2020. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Papers 2007.09043, arXiv.org, revised Mar 2022.
    9. Matthieu Garcin & Jules Klein & Sana Laaribi, 2022. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Working Papers hal-02901988, HAL.
    10. Fourier, Jean-Baptiste Joseph, 2022. "Indicador Bernardos: un nuevo indicador clave en el análisis del mercado de las criptomonedas y de la conducta humana ante lo desconocido," OSF Preprints 87brk, Center for Open Science.
    11. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    12. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    13. Wang, Jianzhou & Hu, Jianming & Ma, Kailiang, 2016. "Wind speed probability distribution estimation and wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 881-899.
    14. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    15. Antonio Squicciarini & Elio Valero Toranzo & Alejandro Zarzo, 2024. "A Time-Series Feature-Extraction Methodology Based on Multiscale Overlapping Windows, Adaptive KDE, and Continuous Entropic and Information Functionals," Mathematics, MDPI, vol. 12(15), pages 1-21, July.
    16. Liu, Wei & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models," Research in International Business and Finance, Elsevier, vol. 54(C).
    17. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Working Papers hal-04102815, HAL.
    18. 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.
    19. Marcin Dec, 2019. "From point through density valuation to individual risk assessment in the discounted cash flows method," GRAPE Working Papers 35, GRAPE Group for Research in Applied Economics.
    20. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).

  12. Andrew Harvey, 2011. "Modelling the Phillips curve with unobserved components," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 7-17.
    See citations under working paper version above.
  13. Fabio Busetti & Andrew Harvey, 2011. "When is a Copula Constant? A Test for Changing Relationships," Journal of Financial Econometrics, Oxford University Press, vol. 9(1), pages 106-131, Winter.
    See citations under working paper version above.
  14. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.

    Cited by:

    1. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    2. Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
    3. Palandri, Alessandro, 2024. "Reconciling interest rates evidence with theory: Rejecting unit roots when the HD(1) is a competing alternative," Journal of Banking & Finance, Elsevier, vol. 161(C).
    4. Denys Pommeret & Laurence Reboul & Anne-francoise Yao, 2023. "Testing the equality of the laws of two strictly stationary processes," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 193-214, April.
    5. Lorenzo Trapani, 2021. "Testing for strict stationarity in a random coefficient autoregressive model," Econometric Reviews, Taylor & Francis Journals, vol. 40(3), pages 220-256, April.
    6. Hart, Jeffrey D., 2016. "A nonparametric test of stationarity for independent data," Statistics & Probability Letters, Elsevier, vol. 108(C), pages 40-44.
    7. Fabio Busetti, 2012. "On detecting end-of-sample instabilities," Temi di discussione (Economic working papers) 881, Bank of Italy, Economic Research and International Relations Area.
    8. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.

  15. Andrew Harvey, 2010. "The local quadratic trend model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 94-108.

    Cited by:

    1. José Luis Cendejas & Félix-Fernando Muñoz & Nadia Fernández-de-Pinedo, 2017. "A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 93-125, January.
    2. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 21184, Victoria University of Wellington, School of Economics and Finance.
    3. Yoon, Gawon, 2015. "Locating change-points in Hodrick–Prescott trends with an application to US real GDP: A generalized unobserved components model approach," Economic Modelling, Elsevier, vol. 45(C), pages 136-141.
    4. Cendejas, José Luis & Castañeda, Juan E. & Muñoz, Félix-Fernando, 2014. "Business cycle, interest rate and money in the euro area: A common factor model," Economic Modelling, Elsevier, vol. 43(C), pages 136-141.
    5. Razek, Noha H.A. & Michieka, Nyakundi M., 2019. "OPEC and non-OPEC production, global demand, and the financialization of oil," Research in International Business and Finance, Elsevier, vol. 50(C), pages 201-225.

  16. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.

    Cited by:

    1. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    2. Mensi, Walid & Selmi, Refk & Al-Yahyaee, Khamis Hamed, 2020. "Switching dependence and systemic risk between crude oil and U.S. Islamic and conventional equity markets: A new evidence," Resources Policy, Elsevier, vol. 69(C).
    3. Andrew Harvey & Stephen Thiele, 2014. "Testing against Changing Correlation," Cambridge Working Papers in Economics 1439, Faculty of Economics, University of Cambridge.
    4. Selmi, Refk & Hammoudeh, Shawkat & Kasmaoui, Kamal & Sousa, Ricardo M. & Errami, Youssef, 2022. "The dual shocks of the COVID-19 and the oil price collapse: A spark or a setback for the circular economy?," Energy Economics, Elsevier, vol. 109(C).
    5. Camirand Lemyre, Felix & Decrouez, Geoffrey, 2021. "Nonparametric recursive estimation of the copula," Statistics & Probability Letters, Elsevier, vol. 168(C).
    6. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    7. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    8. Rémillard, Bruno & Papageorgiou, Nicolas & Soustra, Frédéric, 2012. "Copula-based semiparametric models for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 30-42.
    9. Renée Fry-McKibbin & Vance Martin & Chrismin Tang, 2013. "Financial Contagion and Asset Pricing," CAMA Working Papers 2013-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Selmi, Refk & Wohar, Mark & Deisting, Florent & Kasmaoui, Kamal, 2023. "Dynamic inflation hedging performance and downside risk: A comparison between Islamic and conventional stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 56-67.
    11. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    12. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    13. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).

  17. De Rossi, Giuliano & Harvey, Andrew, 2009. "Quantiles, expectiles and splines," Journal of Econometrics, Elsevier, vol. 152(2), pages 179-185, October.
    See citations under working paper version above.
  18. Harvey, Andrew C. & Delle Monache, Davide, 2009. "Computing the mean square error of unobserved components extracted by misspecified time series models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 283-295, February.

    Cited by:

    1. Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, vol. 230(C).
    2. Matteo Barigozzi & Matteo Luciani, 2024. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Finance and Economics Discussion Series 2024-086, Board of Governors of the Federal Reserve System (U.S.).
    3. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
    4. Flaig Gebhard, 2015. "Why We Should Use High Values for the Smoothing Parameter of the Hodrick-Prescott Filter," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(6), pages 518-538, December.
    5. Rodríguez, Alejandro, 2010. "Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters," DES - Working Papers. Statistics and Econometrics. WS ws100301, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Kristian Jönsson, 2017. "Restricted Hodrick–Prescott filtering in a state-space framework," Empirical Economics, Springer, vol. 53(3), pages 1243-1251, November.
    7. Theofilakou, Nancy & Stournaras, Yannis, 2012. "Current account adjustments in OECD countries revisited: The role of the fiscal stance," Journal of Policy Modeling, Elsevier, vol. 34(5), pages 719-734.
    8. Badarau-Semenescu, Cristina & Ndiaye, Cheikh Tidiane, 2010. "Politique économique et transmission des chocs dans la zone euro," L'Actualité Economique, Société Canadienne de Science Economique, vol. 86(1), pages 35-77, mars.

  19. Busetti, Fabio & Harvey, Andrew, 2008. "Testing For Trend," Econometric Theory, Cambridge University Press, vol. 24(1), pages 72-87, February.
    See citations under working paper version above.
  20. Carvalho, Vasco & Harvey, Andrew & Trimbur, Thomas, 2007. "A Note on Common Cycles, Common Trends, and Convergence," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 12-20, January.

    Cited by:

    1. Bashar, Omar H.M.N. & Bhattacharya, Prasad Sankar & Wohar, Mark E., 2017. "The cyclicality of fiscal policy: New evidence from unobserved components approach," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 222-234.
    2. Onour, Ibrahim, 2010. "Crude Oil Prices and Stock Markets in Major Oil Exporting Countries: Evidence on Decoupling Feature," MPRA Paper 23334, University Library of Munich, Germany.
    3. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    4. Holger Breinlich & Gianmarco I. P. Ottaviano & Jonathan R. W. Temple, 2013. "Regional Growth and Regional Decline," CEP Discussion Papers dp1232, Centre for Economic Performance, LSE.
    5. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2017. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Questioni di Economia e Finanza (Occasional Papers) 382, Bank of Italy, Economic Research and International Relations Area.
    6. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    7. Christian M. Dahl & Henrik Hansen & John Smidt, 2008. "The cyclical component factor model," CREATES Research Papers 2008-44, Department of Economics and Business Economics, Aarhus University.
    8. Omar H. M. N. Bashar, 2015. "The Trickle‐down Effect of the Mining Boom in Australia: Fact or Myth?," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 94-108, June.
    9. Macchiarelli, Corrado, 2013. "GDP-Inflation cyclical similarities in the CEE countries and the euro area," Working Paper Series 1552, European Central Bank.
    10. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    11. Carsten Trenkler & Enzo Weber, 2020. "Identifying shocks to business cycles with asynchronous propagation," Empirical Economics, Springer, vol. 58(4), pages 1815-1836, April.

  21. 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.
    See citations under working paper version above.
  22. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    See citations under working paper version above.
  23. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    See citations under working paper version above.
  24. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.

    Cited by:

    1. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    2. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    3. Borsi, Mihály Tamás & Metiu, Norbert, 2013. "The evolution of economic convergence in the European Union," Discussion Papers 28/2013, Deutsche Bundesbank.
    4. Cesaroni, Tatiana & Maccini, Louis & Malgarini, Marco, 2011. "Business cycle stylized facts and inventory behaviour: New evidence for the Euro area," International Journal of Production Economics, Elsevier, vol. 133(1), pages 12-24, September.
    5. Shushanik Papanyan, 2015. "Digitization and Productivity: Measuring Cycles of Technological Progress," Working Papers 15/33, BBVA Bank, Economic Research Department.
    6. Florentin GLÖTZL & Armon REZAI, 2016. "A sectoral net lending perspective on Europe," Ecological Economics Papers ieep12, Institute of Ecological Economics.
    7. Alka Obadić & Vladimir Arčabić & Lucija Rogić Dumančić, 2021. "Labor market institutions convergence in the European Union," EFZG Working Papers Series 2102, Faculty of Economics and Business, University of Zagreb.
    8. Diegel, Max, 2022. "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers 2022/9, Free University Berlin, School of Business & Economics.
    9. Kozlova, Olesia & de Jesus Noguera, Jose, 2018. "Achievers or slackers? Per capita income trends in European countries," Journal of Policy Modeling, Elsevier, vol. 40(6), pages 1332-1345.
    10. Lucian-Liviu Albu, 2016. "Trends in the relation between regional convergence and economic growth in EU," ERSA conference papers ersa16p244, European Regional Science Association.
    11. Sandra Eickmeier, 2009. "Comovements and heterogeneity in the euro area analyzed in a non-stationary dynamic factor model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 933-959.
    12. 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.
    13. Johnson, Paul & Papageorgiou, Chris, 2018. "What Remains of Cross-Country Convergence?," MPRA Paper 89355, University Library of Munich, Germany.
    14. Carsten Trenkler & Enzo Weber, 2020. "Identifying shocks to business cycles with asynchronous propagation," Empirical Economics, Springer, vol. 58(4), pages 1815-1836, April.
    15. 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).
    16. Mihaela Simionescu, 2015. "About regional convergence clubs in the European Union," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 33(1), pages 67-80.
    17. 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.
    18. Peter Dreuw, 2023. "Structural time series models and synthetic controls—assessing the impact of the euro adoption," Empirical Economics, Springer, vol. 64(2), pages 681-725, February.
    19. ALBU, Lucian – Liviu, 2017. "Budgetary Spending And Growth In The Eu," Journal of Financial and Monetary Economics, Centre of Financial and Monetary Research "Victor Slavescu", vol. 4(1), pages 11-17.
    20. Obadić, Alka & Arčabić, Vladimir & Rogić Dumančić, Lucija, 2023. "Club convergence of labor market institutions in the European Union," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 876-896.
    21. Linda Glawe & Helmut Wagner, 2021. "Divergence Tendencies in the European Integration Process: A Danger for the Sustainability of the E(M)U?," JRFM, MDPI, vol. 14(3), pages 1-22, March.
    22. Ismail Genc & Jon Miller & Anil Rupasingha, 2011. "Stochastic convergence tests for US regional per capita personal income; some further evidence: a research note," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(2), pages 369-377, April.

  25. 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.
    See citations under working paper version above.
  26. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    See citations under working paper version above.
  27. Busetti, Fabio & Harvey, Andrew, 2003. "Seasonality Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 420-436, July.

    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. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    3. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    4. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    5. Stefano Grassi & Tommaso Proietti, 2011. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," CREATES Research Papers 2011-30, Department of Economics and Business Economics, Aarhus University.
    6. Irma Hindrayanto & John A.D. Aston & Siem Jan Koopman & Marius Ooms, 2013. "Modelling trigonometric seasonal components for monthly economic time series," Applied Economics, Taylor & Francis Journals, vol. 45(21), pages 3024-3034, July.
    7. 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.
    8. 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.
    9. 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.
    10. Tommaso, Proietti & Stefano, Grassi, 2010. "Bayesian stochastic model specification search for seasonal and calendar effects," MPRA Paper 27305, University Library of Munich, Germany.
    11. E. Andersson & D. Bock & M. Frisen, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 257-278.
    12. 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.
    13. 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.
    14. Tommaso Proietti & Cecilia Frale, 2007. "New proposals for the quantification of qualitative survey data," CEIS Research Paper 98, Tor Vergata University, CEIS.
    15. 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.
    16. Webel, Karsten, 2016. "A data-driven selection of an appropriate seasonal adjustment approach," Discussion Papers 07/2016, Deutsche Bundesbank.
    17. 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.
    18. Fabio Busetti & Silvestro di Sanzo, 2011. "Bootstrap LR tests of stationarity, common trends and cointegration," Temi di discussione (Economic working papers) 799, Bank of Italy, Economic Research and International Relations Area.
    19. Apergis, Nicholas & Lau, Marco Chi Keung, 2015. "Structural breaks and electricity prices: Further evidence on the role of climate policy uncertainties in the Australian electricity market," Energy Economics, Elsevier, vol. 52(PA), pages 176-182.

  28. Fabio Busetti & Andrew Harvey, 2003. "Further Comments On Stationarity Tests In Series With Structural Breaks At Unknown Points," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 137-140, March.

    Cited by:

    1. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    2. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Working Papers 0043, Gaidar Institute for Economic Policy, revised 2013.
    3. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    4. Rabah Arezki & Kaddour Hadri & Eiji Kurozumi & Yao Rao, 2012. "Breaking the Prebish Singer Hypothesis using Panel Data Stationarity Tests," Economics Working Papers 12-01, Queen's Management School, Queen's University Belfast.
    5. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion - in Russian," Working Papers 0044, Gaidar Institute for Economic Policy, revised 2012.
    6. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    7. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    8. 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.
    9. Kaddour Hadri & Rolf Larsson & Yao Rao, 2012. "Testing For Stationarity With A Break In Panels Where The Time Dimension Is Finite," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 123-148, December.
    10. 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.
    11. Kaddour Hadri & Yao Rao, 2008. "Panel Stationarity Test with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 245-269, April.
    12. David I. Harvey & Terence C. Mills, 2004. "Tests for Stationarity in Series with Endogenously Determined Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 863-894, December.
    13. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    14. 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.
    15. Arezki, Rabah & Hadri, Kaddour & Kurozumi, Eiji & Rao, Yao, 2012. "Testing the Prebish–Singer hypothesis using second-generation panel data stationarity tests with a break," Economics Letters, Elsevier, vol. 117(3), pages 814-816.

  29. Andrew Harvey & Jared Bernstein, 2003. "Measurement and Testing of Inequality from Time Series of Deciles with an Application to U.S. Wages," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 141-152, February.
    See citations under working paper version above.
  30. Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May.
    See citations under working paper version above.
  31. Fabio Busetti & Andrew Harvey, 2001. "Testing for the Presence of a Random Walk in Series with Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(2), pages 127-150, March.
    See citations under working paper version above.
  32. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.

    Cited by:

    1. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2002. "Unity and Plurality of the European Cycle," Documents de Travail de l'OFCE 2002-03, Observatoire Francais des Conjonctures Economiques (OFCE).
    2. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    3. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    4. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    5. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    6. Christopher Klein & Shea Slonaker, 2010. "Chart Turnover and Sales in the Recorded Music Industry: 1990–2005," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 36(4), pages 351-372, June.
    7. Shahriyar Mukhtarov & Jeyhun I. Mikayilov & Sugra Humbatova & Vugar Muradov, 2020. "Do High Oil Prices Obstruct the Transition to Renewable Energy Consumption?," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    8. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    9. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    10. Ferrara, L. & Koopman, S J., 2010. "Common business and housing market cycles in the Euro area from a multivariate decomposition," Working papers 275, Banque de France.
    11. Xiaoshan Chen & Terence Mills, 2012. "Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts," Empirical Economics, Springer, vol. 43(2), pages 671-692, October.
    12. Chen, Xiaoshan & MacDonald, Ronald, 2010. "Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models," SIRE Discussion Papers 2010-41, Scottish Institute for Research in Economics (SIRE).
    13. Siem Jan Koopman & André Lucas & Marius Ooms & Kees van Montfort & Victor van der Geest, 2007. "Estimating Systematic Continuous-time Trends in Recidivism using a Non-Gaussian Panel Data Model," Tinbergen Institute Discussion Papers 07-027/4, Tinbergen Institute.
    14. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    15. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    16. 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.
    17. Xiaoyi Mu and Haichun Ye, 2015. "Small Trends and Big Cycles in Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    18. Mikayilov, Jeyhun I. & Darandary, Abdulelah & Alyamani, Ryan & Hasanov, Fakhri J. & Alatawi, Hatem, 2020. "Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand," Energy Policy, Elsevier, vol. 146(C).

  33. Harvey, Andrew, 2001. "Testing in Unobserved Components Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(1), pages 1-19, January.

    Cited by:

    1. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    2. Tommaso Proietti, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Econometrics 0209002, University Library of Munich, Germany.
    3. Stefano Grassi & Tommaso Proietti, 2011. "Characterizing economic trends by Bayesian stochastic model specification search," CREATES Research Papers 2011-16, Department of Economics and Business Economics, Aarhus University.
    4. Webel, Karsten & Smyk, Anna, 2023. "Towards seasonal adjustment of infra-monthly time series with JDemetra+," Discussion Papers 24/2023, Deutsche Bundesbank.
    5. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    6. Bruno, Giancarlo & Malgarini, Marco, 2002. "An Indicator of Economic Sentiment for the Italian Economy," MPRA Paper 42331, University Library of Munich, Germany.
    7. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    8. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2005. "Trends and cycles in economic time series: A Bayesian approach," Econometric Institute Research Papers EI 2005-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Guro Børnes Ringlund & Knut Einar Rosendahl & Terje Skjerpen, 2004. "Does oilrig activity react to oil price changes? An empirical investigation," Discussion Papers 372, Statistics Norway, Research Department.
    10. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    11. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    12. Irma Hindrayanto & John A.D. Aston & Siem Jan Koopman & Marius Ooms, 2013. "Modelling trigonometric seasonal components for monthly economic time series," Applied Economics, Taylor & Francis Journals, vol. 45(21), pages 3024-3034, July.
    13. 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.
    14. 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.
    15. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Peter R. Hansen & Asger Lunde, 2010. "Estimating the Persistence and the Autocorrelation Function of a Time Series that is Measured with Error," CREATES Research Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
    17. Fausto Hern'andez Trillo & C. Vladimir Rodr'iguez-Caballero & Daniel Ventosa-Santaul`aria, 2024. "Monopoly Unveiled: Telecom Breakups in the US and Mexico," Papers 2407.09695, arXiv.org.
    18. Christophe Planas & Alessandro Rossi & Gabriele Fiorentini, 2008. "The marginal likelihood of Structural Time Series Models, with application to the euro area and US NAIRU," Working Paper series 21_08, Rimini Centre for Economic Analysis.
    19. Matei Demetrescu & Uwe Hassler & Adina Tarcolea, 2010. "Testing for stationarity in large panels with cross-dependence, and US evidence on unit labor cost," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(8), pages 1381-1397.
    20. Frits Bijleveld & Jacques Commandeur & Phillip Gould & Siem Jan Koopman, 2008. "Model‐based measurement of latent risk in time series with applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 265-277, January.
    21. Filippo Ferroni & Stefano Grassi & Miguel A. Leon-Ledesma, 2015. "Fundamental shock selection in DSGE models," Studies in Economics 1508, School of Economics, University of Kent.
    22. Patrick Wilson & Simon Stevenson & Ralf Zurbruegg, 2007. "Foreign Property Shocks and the Impact on Domestic Securitized Real Estate Markets: An Unobserved Components Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 34(3), pages 407-424, April.
    23. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    24. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.

  34. Nyblom, Jukka & Harvey, Andrew, 2000. "Tests Of Common Stochastic Trends," Econometric Theory, Cambridge University Press, vol. 16(2), pages 176-199, April.
    See citations under working paper version above.
  35. Andrew Harvey & Siem Jan Koopman, 2000. "Signal extraction and the formulation of unobserved components models," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 84-107.
    See citations under working paper version above.
  36. Proietti, Tommaso & Harvey, Andrew, 2000. "A Beveridge-Nelson smoother," Economics Letters, Elsevier, vol. 67(2), pages 139-146, May.

    Cited by:

    1. Tommaso Proietti, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Econometrics 0209002, University Library of Munich, Germany.
    2. Kum Hwa Oh & Eric Zivot & Drew Creal, 2006. "The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks," Working Papers UWEC-2006-16-FC, University of Washington, Department of Economics.
    3. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    4. Proietti, Tommaso, 2011. "The Multistep Beveridge-Nelson Decomposition," Working Papers 09/2011, University of Sydney Business School, Discipline of Business Analytics.
    5. Stefano Grassi & Tommaso Proietti, 2011. "Characterizing economic trends by Bayesian stochastic model specification search," CREATES Research Papers 2011-16, Department of Economics and Business Economics, Aarhus University.
    6. Proietti, Tommaso, 2008. "Direct and iterated multistep AR methods for difference stationary processes," MPRA Paper 10859, University Library of Munich, Germany.
    7. J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
    8. Tommaso Proietti, 2005. "Forecasting and signal extraction with misspecified models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 539-556.
    9. André Nunes Maranhão, 2024. "Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(1), pages 1-58, August.
    10. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.

  37. Andrew Harvey & Chia‐Hui Chung, 2000. "Estimating the underlying change in unemployment in the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 303-309.

    Cited by:

    1. Du, Rex Yuxing & Kamakura, Wagner A., 2015. "Improving the statistical performance of tracking studies based on repeated cross-sections with primary dynamic factor analysis," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 94-112.
    2. Andrew C. Harvey, 2020. "Time series models for epidemics: leading indicators, control groups and policy assessment," National Institute of Economic and Social Research (NIESR) Discussion Papers 517, National Institute of Economic and Social Research.
    3. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
    4. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    5. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
    7. Caio Gonçalves & Luna Hidalgo & Denise Silva & Jan van den Brakel, 2022. "Single‐month unemployment rate estimates for the Brazilian Labour Force Survey using state‐space models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1707-1732, October.
    8. Caterina Schiavoni & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2019. "A dynamic factor model approach to incorporate Big Data in state space models for official statistics," Papers 1901.11355, arXiv.org, revised Feb 2020.
    9. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    10. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
    11. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    12. Laura Bisio & Filippo Moauro, 2018. "Temporal disaggregation by dynamic regressions: Recent developments in Italian quarterly national accounts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 471-494, November.
    13. Jo Thori Lind, 2002. "Small continuous surveys and the Kalman filter," Discussion Papers 333, Statistics Norway, Research Department.
    14. Pérez, Javier J. & Pedregal, Diego J., 2008. "Should quarterly government finance statistics be used for fiscal surveillane in Europe?," Working Paper Series 937, European Central Bank.
    15. Eliana González & Luis F. Melo & Luis E. Rojas & Brayan Rojas, 2010. "Estimations of the natural rate of interest in Colombia," Borradores de Economia 626, Banco de la Republica de Colombia.
    16. Jo Thori Lind, 2005. "Repeated surveys and the Kalman filter," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 418-427, December.
    17. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    18. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2009. "Survey Data as Coicident or Leading Indicators," Economics Working Papers ECO2009/19, European University Institute.
    19. A. C. Harvey & Siem Jan Koopman, 2000. "Computing Observation Weights for Signal Extraction and Filtering," Econometric Society World Congress 2000 Contributed Papers 0888, Econometric Society.
    20. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.
    21. Wanger, Susanne & Weigand, Roland & Zapf, Ines, 2014. "Revision der IAB-Arbeitszeitrechnung 2014 : Grundlagen, methodische Weiterentwicklungen sowie ausgewählte Ergebnisse im Rahmen der Revision der Volkswirtschaftlichen Gesamtrechnungen," IAB-Forschungsbericht 201409, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    22. Rolando Peláez, 2012. "The housing bubble in real-time: the end of innocence," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 211-225, January.
    23. Viv Hall & John McDermott, 2007. "A Quarterly Post-World War II Real GDP Series for New Zealand," Working Papers 07_13, Motu Economic and Public Policy Research.
    24. Fabio H. Nieto & Luis Fernando Melo, 2001. "About a Coincidente Index for the State of the Economy," Borradores de Economia 194, Banco de la Republica de Colombia.
    25. Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
    26. Veenstra, Joost, 2015. "Output growth in German manufacturing, 1907–1936. A reinterpretation of time-series evidence," Explorations in Economic History, Elsevier, vol. 57(C), pages 38-49.
    27. Tommaso Proietti, 2004. "Temporal Disaggregation by State Space Methods: Dynamic Regression Methods Revisited," Econometrics 0411011, University Library of Munich, Germany.
    28. Francisco de Castro & Francisco Martí & Antonio Montesinos & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "Fiscal policies in Spain: Main stylises facts revisited," Working Papers 1408, Banco de España.
    29. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    30. David Leuwer & Bernd Süssmuth, 2018. "Assessing Temporary Product-Specific Subsidies: A Time Series Intervention Analysis," CESifo Working Paper Series 6946, CESifo.
    31. Nicholas T. Longford, 2004. "Missing data and small area estimation in the UK Labour Force Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(2), pages 341-373, May.
    32. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.
    33. Jaworski Stanisław, 2020. "A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 41-52, June.
    34. Javier Pérez & A. Sánchez, 2011. "Is there a signalling role for public wages? Evidence for the euro area based on macro data," Empirical Economics, Springer, vol. 41(2), pages 421-445, October.
    35. Víctor Gómez & Félix Aparicio‐Pérez, 2009. "A new state–space methodology to disaggregate multivariate time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 97-124, January.
    36. Jan A. Brakel & Sabine Krieg, 2016. "Small area estimation with state space common factor models for rotating panels," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 763-791, June.
    37. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
    38. Orair, Rodrigo Octávio & Silva, Wesley de Jesus, 2013. "Subnational Government Investment in Brazil: Estimation and Analysis by State Space Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(1), September.
    39. Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
    40. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.
    41. Krieg, Sabine & van den Brakel, Jan A., 2012. "Estimation of the monthly unemployment rate for six domains through structural time series modelling with cointegrated trends," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2918-2933.
    42. Joan Paredes & Diego J. Pedregal & Javier J. Pérez, 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Papers 0935, Banco de España.
    43. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    44. Pedregal, D.J. & Dejuán, O. & Gómez, N. & Tobarra, M.A., 2009. "Modelling demand for crude oil products in Spain," Energy Policy, Elsevier, vol. 37(11), pages 4417-4427, November.
    45. Xinshuai Dong & Haoyue Dai & Yewen Fan & Songyao Jin & Sathyamoorthy Rajendran & Kun Zhang, 2023. "On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors," Papers 2401.05414, arXiv.org, revised Jan 2024.
    46. Tommaso Proietti, 2007. "Band Spectral Estimation for Signal Extraction," CEIS Research Paper 104, Tor Vergata University, CEIS.
    47. Andrew C. Harvey, 2002. "Trends, Cycles, and Convergence," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.),Economic Growth: Sources, Trends, and Cycles, edition 1, volume 6, chapter 8, pages 221-250, Central Bank of Chile.
    48. Danny Pfeffermann, 2022. "Time series modelling of repeated survey data for estimation of finite population parameters," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1757-1777, October.
    49. Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.
    50. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
    51. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(1), pages 97-119, March.

  38. Andrew Harvey & Mariane Streibel, 1998. "Tests for Deterministic Versus Indeterministic Cycles," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(5), pages 505-529, September.

    Cited by:

    1. Marczak, Martyna & Beissinger, Thomas, 2010. "Real Wages and the Business Cycle in Germany," IZA Discussion Papers 5199, Institute of Labor Economics (IZA).
    2. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.

  39. Harvey, Andrew & Streibel, Mariane, 1998. "Testing for a slowly changing level with special reference to stochastic volatility," Journal of Econometrics, Elsevier, vol. 87(1), pages 167-189, August.

    Cited by:

    1. Broto, Carmen, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2021. "Modeling and forecasting macroeconomic downside risk," Temi di discussione (Economic working papers) 1324, Bank of Italy, Economic Research and International Relations Area.
    3. Poncela, Pilar, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    5. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    6. David McMillan, 2001. "Common stochastic volatility trend in European exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 8(9), pages 605-608.
    7. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    8. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342.
    9. Alin Sima, 2008. "Stylized Facts and Discrete Stochastic Volatility Models," Advances in Economic and Financial Research - DOFIN Working Paper Series 10, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    10. Andrew Harvey & Stephen Thiele, 2014. "Testing against Changing Correlation," Cambridge Working Papers in Economics 1439, Faculty of Economics, University of Cambridge.
    11. Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
    12. 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.
    13. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    14. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    15. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    16. Mora Galán, Alberto & Pérez, Ana, 2004. "Stochastic volatility models and the Taylor effect," DES - Working Papers. Statistics and Econometrics. WS ws046315, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Pena, Daniel & Rodriguez, Julio, 2005. "Detecting nonlinearity in time series by model selection criteria," International Journal of Forecasting, Elsevier, vol. 21(4), pages 731-748.

  40. Harvey, Andrew & Koopman, Siem Jan & Riani, Marco, 1997. "The Modeling and Seasonal Adjustment of Weekly Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 354-368, July.

    Cited by:

    1. Juan Sebastián Becerra C. & Luis Ceballos S. & Felipe Córdova F. & Michael Pedersen, 2010. "Market Interest Rate Dynamics in Times of Financial Turmoil," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 13(1), pages 5-22, April.
    2. Martin-Rodriguez, Gloria & Caceres-Hernandez, Jose Juan, 2012. "Forecasting weekly Canary tomato exports from annual surface data," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126364, International Association of Agricultural Economists.
    3. Cabrero, Alberto & Camba-Méndez, Gonzalo & Hirsch, Astrid & Nieto, Fernando, 2002. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Working Paper Series 142, European Central Bank.
    4. Barend Abeln & Jan P.A.M. Jacobs, 2021. "COVID-19 and seasonal adjustment," CAMA Working Papers 2021-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
    6. Webel, Karsten & Smyk, Anna, 2023. "Towards seasonal adjustment of infra-monthly time series with JDemetra+," Discussion Papers 24/2023, Deutsche Bundesbank.
    7. Ralf Dewenter & Ulrich Heimeshoff, 2017. "Predicting Advertising Volumes Using Structural Time Series Models: A Case Study," Economics Bulletin, AccessEcon, vol. 37(3), pages 1644-1652.
    8. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    9. Chen Zhen & Mary Muth & Abigail Okrent & Shawn Karns & Derick Brown & Peter Siegel, 2019. "Do differences in reported expenditures between household scanner data and expenditure surveys matter in health policy research?," Health Economics, John Wiley & Sons, Ltd., vol. 28(6), pages 782-800, June.
    10. Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
    11. Rodriguez, Gloria Martin & Hernandez, Jose Juan Caceres, 2005. "Evolving Seasonal Pattern of Tenerife Tomato Exports," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24501, European Association of Agricultural Economists.
    12. 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.
    13. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    14. Guerino Ardizzi & Simone Emiliozzi & Juri Marcucci & Libero Monteforte, 2019. "News and consumer card payments," Temi di discussione (Economic working papers) 1233, Bank of Italy, Economic Research and International Relations Area.
    15. Dewenter, Ralf & Heimeshoff, Ulrich, 2016. "Predicting advertising volumes: A structural time series approach," DICE Discussion Papers 228, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    16. Jose Juan Caceres-Hernandez & Gloria Martin-Rodriguez & Jonay Hernandez-Martin, 2022. "A proposal for measuring and comparing seasonal variations in hourly economic time series," Empirical Economics, Springer, vol. 62(4), pages 1995-2021, April.
    17. Martin-Rodriguez, Gloria & Caceres-Hernandez, Jose Juan, 2009. "The Proportion of the Seasonal Period as a Season Index in Weekly Agricultural Data," 2009 Conference, August 16-22, 2009, Beijing, China 49956, International Association of Agricultural Economists.
    18. Joao Tovar Jalles, 2009. "Structural time series models and the Kalman filter: a concise review," Nova SBE Working Paper Series wp541, Universidade Nova de Lisboa, Nova School of Business and Economics.
    19. García, Juan R. & Pacce, Matías & Rodrigo, Tomasa & Ruiz de Aguirre, Pep & Ulloa, Camilo A., 2021. "Measuring and forecasting retail trade in real time using card transactional data," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1235-1246.
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    21. Kaushik Bhattacharya & Sunny Kumar Singh, 2016. "Impact of Payment Technology on Seasonality of Currency in Circulation: Evidence from the USA and India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 117-136, June.
    22. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
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    24. Caceres-Hernandez, Jose & Martin-Rodriguez, Gloria, 2015. "Splines and seasonal unit roots in weekly agricultural prices," 2015 Conference, August 9-14, 2015, Milan, Italy 211380, International Association of Agricultural Economists.
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    1. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
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    6. Ishmael Ackah, 2014. "Determinants of natural gas demand in Ghana," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 272-295, September.
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    1. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Jiang, G.J. & van der Sluis, P.J., 2000. "Index Option Pricing Models with Stochastic Volatility and Stochastic Interest Rates," Discussion Paper 2000-36, Tilburg University, Center for Economic Research.
    3. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques.
    4. Jensen Mark J., 2016. "Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 455-475, September.
    5. Mauro Bernardi & Leopoldo Catania, 2014. "The Model Confidence Set package for R," Papers 1410.8504, arXiv.org.
    6. Márcio Laurini, 2012. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," IBMEC RJ Economics Discussion Papers 2012-02, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    7. Isabel Casas & Helena Veiga, 2021. "Exploring Option Pricing and Hedging via Volatility Asymmetry," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1015-1039, April.
    8. Bermudez, P. de Zea & Marín, J. Miguel & Rue, Håvard & Veiga, Helena, 2024. "Integrated nested Laplace approximations for threshold stochastic volatility models," Econometrics and Statistics, Elsevier, vol. 30(C), pages 15-35.
    9. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
    10. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    11. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," Tinbergen Institute Discussion Papers 13-003/III, Tinbergen Institute.
    12. Nguyen, Hoang & Nguyen, Trong-Nghia & Tran, Minh-Ngoc, 2021. "A dynamic leverage stochastic volatility model," Working Papers 2021:14, Örebro University, School of Business.
    13. Helena Veiga, 2009. "Financial Stylized Facts and the Taylor-Effect in Stochastic Volatility Models," Economics Bulletin, AccessEcon, vol. 29(1), pages 265-276.
    14. Broto, Carmen, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Pascale VALERY (HEC-Montreal) & Jean-Marie Dufour (University of Montreal), 2004. "A simple estimation method and finite-sample inference for a stochastic volatility model," Econometric Society 2004 North American Summer Meetings 153, Econometric Society.
    16. Faruk Selcuk, 2005. "Asymmetric stochastic volatility in emerging stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 15(12), pages 867-874.
    17. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
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    1. Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean-Marc Tallon, 2018. "Ambiguity and the historical equity premium," Post-Print halshs-01886571, HAL.
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    4. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
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    1. Iñaki Bildosola & Pilar Gonzalez & Paz Moral, 2017. "An approach for modelling and forecasting research activity related to an emerging technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 557-572, July.
    2. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
    3. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.
    4. K. Triantafyllopoulos, 2007. "Covariance estimation for multivariate conditionally Gaussian dynamic linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 551-569.
    5. Alejandro Ferrer Pérez & José Casals Carro & Sonia Sotoca López, 2014. "Linking the problems of estimating and allocating unconditional capital," Documentos de Trabajo del ICAE 2014-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    6. Yoshida, Wataru & Hirose, Kei, 2024. "Fast same-step forecast in SUTSE model and its theoretical properties," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
    7. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
    8. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.

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    1. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    2. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    3. McCrorie, J.R. & Chambers, M.J., 2004. "Granger Causality and the Sampling of Economic Processes," Discussion Paper 2004-39, Tilburg University, Center for Economic Research.
    4. Mariusz Maziarz, 2015. "A review of the Granger-causality fallacy," The Journal of Philosophical Economics, Bucharest Academy of Economic Studies, The Journal of Philosophical Economics, vol. 8(2), May.
    5. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    6. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    7. Jewitt, Giles & Roderick McCrorie, J., 2005. "Computing estimates of continuous time macroeconometric models on the basis of discrete data," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 397-416, April.
    8. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2014. "Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data," CESifo Working Paper Series 5030, CESifo.
    9. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.

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    1. Godolphin, E.J. & Triantafyllopoulos, Kostas, 2006. "Decomposition of time series models in state-space form," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2232-2246, May.
    2. Kostas Triantafyllopoulos, 2009. "Inference of Dynamic Generalized Linear Models: On‐Line Computation and Appraisal," International Statistical Review, International Statistical Institute, vol. 77(3), pages 430-450, December.
    3. Thiago R. Santos & Glaura C. Franco & Dani Gamerman, 2010. "Comparison of Classical and Bayesian Approaches for Intervention Analysis," International Statistical Review, International Statistical Institute, vol. 78(2), pages 218-239, August.
    4. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Other publications TiSEM 6338af09-6f2c-46d0-985b-d, Tilburg University, School of Economics and Management.
    6. de Pinho, Frank M. & Franco, Glaura C. & Silva, Ralph S., 2016. "Modeling volatility using state space models with heavy tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 108-127.
    7. Wu, Rongning, 2012. "On variance estimation in a negative binomial time series regression model," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 145-155.
    8. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    9. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    10. Nobuhiko Terui & Masataka Ban, 2013. "Multivariate Time Series Model with Hierarchical Structure for Over-dispersed Discrete Outcomes," TMARG Discussion Papers 113, Graduate School of Economics and Management, Tohoku University, revised Aug 2013.
    11. Yelland, Phillip M., 2009. "Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management," International Journal of Production Economics, Elsevier, vol. 118(1), pages 95-103, March.
    12. Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
    13. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    14. Dani Gamerman & Thiago Rezende Santos & Glaura C. Franco, 2013. "A Non-Gaussian Family Of State-Space Models With Exact Marginal Likelihood," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 625-645, November.
    15. Richard A. Davis & Thomas C. M. Lee & Gabriel A. Rodriguez‐Yam, 2008. "Break Detection for a Class of Nonlinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 834-867, September.
    16. Shang, Zuofeng, 2012. "On latent process models in multi-dimensional space," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1259-1266.
    17. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.
    18. Yang Lu, 2018. "Dynamic Frailty Count Process in Insurance: A Unified Framework for Estimation, Pricing, and Forecasting," Post-Print halshs-02418950, HAL.
    19. Ralph Snyder & Adrian Beaumont & J. Keith Ord, 2012. "Intermittent demand forecasting for inventory control: A multi-series approach," Monash Econometrics and Business Statistics Working Papers 15/12, Monash University, Department of Econometrics and Business Statistics.
    20. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    21. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    22. Ki Hong Kim & Young Jae Han & Sugil Lee & Sung Won Cho & Chulung Lee, 2019. "Text Mining for Patent Analysis to Forecast Emerging Technologies in Wireless Power Transfer," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    23. Denuit, Michel & Lu, Yang, 2020. "Wishart-Gamma mixtures for multiperil experience ratemaking, frequency-severity experience rating and micro-loss reserving," LIDAM Discussion Papers ISBA 2020016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    24. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    25. Youn Ahn, Jae & Jeong, Himchan & Lu, Yang, 2021. "On the ordering of credibility factors," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 626-638.
    26. Higuchi, Tomoyuki, 1999. "Applications of quasi-periodic oscillation models to seasonal small count time series," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 281-301, May.
    27. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    28. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    29. AKINYEMI, Emmanuel K & OGUNLEYE, Abiodun O & GUNSOLA, Obaseye A & Olaoye, Hakeem O, 2021. "Modelling Theft Criminal Offence in Kwara State Using ARIMA," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(4), pages 177-182, April.
    30. Jean Peyhardi, 2024. "Integer-valued autoregressive models based on quasi Pólya thinning operator," Statistical Inference for Stochastic Processes, Springer, vol. 27(3), pages 813-838, October.
    31. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    32. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    33. Heinen, Andreas, 2003. "Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model," MPRA Paper 8113, University Library of Munich, Germany.
    34. Nobuhiko Terui & Masataka Ban & Toshihiko Maki, 2010. "Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 91-107, February.
    35. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    36. Marzo, Massimiliano & Zagaglia, Paolo, 2014. "Asymmetric information and term lending in the Euro money market: Evidence from the beginning of the turmoil," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 487-499.
    37. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    38. Marcelo Bourguignon & Christian H. Weiß, 2017. "An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 847-868, December.
    39. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    40. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    41. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    42. Abdallah, Anas & Boucher, Jean-Philippe & Cossette, Hélène, 2016. "Sarmanov family of multivariate distributions for bivariate dynamic claim counts model," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 120-133.
    43. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    44. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    45. Sean P. O'brien, 1996. "Foreign Policy Crises and the Resort to Terrorism," Journal of Conflict Resolution, Peace Science Society (International), vol. 40(2), pages 320-335, June.
    46. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    47. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    48. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    49. Eunsuk Chun & Sungchan Jun & Chulung Lee, 2021. "Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    50. Tevfik Aktekin & Nicholas G. Polson & Refik Soyer, 2020. "A family of multivariate non‐gaussian time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 691-721, September.
    51. Kuk, Anthony Y. C., 1999. "The use of approximating models in Monte Carlo maximum likelihood estimation," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 325-333, December.
    52. J. K. Lindsey, 2001. "A family of repeated measurements models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 3-9, January.
    53. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.
    54. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    55. Brannas, Kurt, 1995. "Prediction and control for a time-series count data model," International Journal of Forecasting, Elsevier, vol. 11(2), pages 263-270, June.
    56. Svetunkov, Ivan & Boylan, John E., 2023. "iETS: State space model for intermittent demand forecasting," International Journal of Production Economics, Elsevier, vol. 265(C).

  56. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 422-422, October.

    Cited by:

    1. Godolphin, E.J. & Triantafyllopoulos, Kostas, 2006. "Decomposition of time series models in state-space form," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2232-2246, May.
    2. Kostas Triantafyllopoulos, 2009. "Inference of Dynamic Generalized Linear Models: On‐Line Computation and Appraisal," International Statistical Review, International Statistical Institute, vol. 77(3), pages 430-450, December.
    3. Thiago R. Santos & Glaura C. Franco & Dani Gamerman, 2010. "Comparison of Classical and Bayesian Approaches for Intervention Analysis," International Statistical Review, International Statistical Institute, vol. 78(2), pages 218-239, August.
    4. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Other publications TiSEM 6338af09-6f2c-46d0-985b-d, Tilburg University, School of Economics and Management.
    6. de Pinho, Frank M. & Franco, Glaura C. & Silva, Ralph S., 2016. "Modeling volatility using state space models with heavy tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 108-127.
    7. Wu, Rongning, 2012. "On variance estimation in a negative binomial time series regression model," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 145-155.
    8. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    9. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    10. Nobuhiko Terui & Masataka Ban, 2013. "Multivariate Time Series Model with Hierarchical Structure for Over-dispersed Discrete Outcomes," TMARG Discussion Papers 113, Graduate School of Economics and Management, Tohoku University, revised Aug 2013.
    11. Yelland, Phillip M., 2009. "Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management," International Journal of Production Economics, Elsevier, vol. 118(1), pages 95-103, March.
    12. Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
    13. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    14. Dani Gamerman & Thiago Rezende Santos & Glaura C. Franco, 2013. "A Non-Gaussian Family Of State-Space Models With Exact Marginal Likelihood," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 625-645, November.
    15. Richard A. Davis & Thomas C. M. Lee & Gabriel A. Rodriguez‐Yam, 2008. "Break Detection for a Class of Nonlinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 834-867, September.
    16. Shang, Zuofeng, 2012. "On latent process models in multi-dimensional space," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1259-1266.
    17. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.
    18. Yang Lu, 2018. "Dynamic Frailty Count Process in Insurance: A Unified Framework for Estimation, Pricing, and Forecasting," Post-Print halshs-02418950, HAL.
    19. Ralph Snyder & Adrian Beaumont & J. Keith Ord, 2012. "Intermittent demand forecasting for inventory control: A multi-series approach," Monash Econometrics and Business Statistics Working Papers 15/12, Monash University, Department of Econometrics and Business Statistics.
    20. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    21. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    22. Ki Hong Kim & Young Jae Han & Sugil Lee & Sung Won Cho & Chulung Lee, 2019. "Text Mining for Patent Analysis to Forecast Emerging Technologies in Wireless Power Transfer," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    23. Denuit, Michel & Lu, Yang, 2020. "Wishart-Gamma mixtures for multiperil experience ratemaking, frequency-severity experience rating and micro-loss reserving," LIDAM Discussion Papers ISBA 2020016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    24. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    25. Youn Ahn, Jae & Jeong, Himchan & Lu, Yang, 2021. "On the ordering of credibility factors," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 626-638.
    26. Higuchi, Tomoyuki, 1999. "Applications of quasi-periodic oscillation models to seasonal small count time series," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 281-301, May.
    27. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    28. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    29. AKINYEMI, Emmanuel K & OGUNLEYE, Abiodun O & GUNSOLA, Obaseye A & Olaoye, Hakeem O, 2021. "Modelling Theft Criminal Offence in Kwara State Using ARIMA," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(4), pages 177-182, April.
    30. Jean Peyhardi, 2024. "Integer-valued autoregressive models based on quasi Pólya thinning operator," Statistical Inference for Stochastic Processes, Springer, vol. 27(3), pages 813-838, October.
    31. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    32. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    33. Heinen, Andreas, 2003. "Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model," MPRA Paper 8113, University Library of Munich, Germany.
    34. Nobuhiko Terui & Masataka Ban & Toshihiko Maki, 2010. "Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 91-107, February.
    35. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    36. Marzo, Massimiliano & Zagaglia, Paolo, 2014. "Asymmetric information and term lending in the Euro money market: Evidence from the beginning of the turmoil," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 487-499.
    37. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    38. Marcelo Bourguignon & Christian H. Weiß, 2017. "An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 847-868, December.
    39. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    40. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    41. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    42. Abdallah, Anas & Boucher, Jean-Philippe & Cossette, Hélène, 2016. "Sarmanov family of multivariate distributions for bivariate dynamic claim counts model," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 120-133.
    43. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    44. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    45. Sean P. O'brien, 1996. "Foreign Policy Crises and the Resort to Terrorism," Journal of Conflict Resolution, Peace Science Society (International), vol. 40(2), pages 320-335, June.
    46. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    47. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    48. Eunsuk Chun & Sungchan Jun & Chulung Lee, 2021. "Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    49. Tevfik Aktekin & Nicholas G. Polson & Refik Soyer, 2020. "A family of multivariate non‐gaussian time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 691-721, September.
    50. Kuk, Anthony Y. C., 1999. "The use of approximating models in Monte Carlo maximum likelihood estimation," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 325-333, December.
    51. J. K. Lindsey, 2001. "A family of repeated measurements models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 3-9, January.
    52. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.
    53. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    54. Brannas, Kurt, 1995. "Prediction and control for a time-series count data model," International Journal of Forecasting, Elsevier, vol. 11(2), pages 263-270, June.
    55. Svetunkov, Ivan & Boylan, John E., 2023. "iETS: State space model for intermittent demand forecasting," International Journal of Production Economics, Elsevier, vol. 265(C).

  57. A. C. Harvey & P. M. Robinson, 1988. "Efficient Estimation Of Nonstationary Time Series Regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(3), pages 201-214, May.

    Cited by:

    1. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    2. Zhang, Erhua & Wu, Jilin, 2020. "Adaptive estimation of AR∞ models with time-varying variances," Economics Letters, Elsevier, vol. 197(C).
    3. Yoshihiro Usami & Mituaki Huzii, 1995. "Estimation Of Coefficients Of Time Series Regression With A Nonstationary Error Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(1), pages 105-118, January.
    4. 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.

  58. Harvey, A. C. & Stock, James H., 1988. "Continuous time autoregressive models with common stochastic trends," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 365-384.

    Cited by:

    1. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    2. Martin Schmidt, 2003. "The relative adjustment of wages and prices: direct tests within a multiple-equation system," Applied Economics, Taylor & Francis Journals, vol. 35(8), pages 985-997.
    3. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    4. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    5. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.
    6. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2017. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 81869, London School of Economics and Political Science, LSE Library.
    7. Schmidt, Martin B., 2001. "The long and short of money and prices: a market equilibrium approach," Journal of Economics and Business, Elsevier, vol. 53(6), pages 563-583.
    8. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    9. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    10. Timothy Cogley, "undated". "How Fast Can the New Economy Grow? A Bayesian Analysis of the Evolution of Trend Growth," Working Papers 2133301, Department of Economics, W. P. Carey School of Business, Arizona State University.
    11. Joann Jasiak, 2003. "First‐Order Autoregressive Processes with Heterogeneous Persistence," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(3), pages 283-309, May.
    12. Francesco Giuli & Massimiliano Tancioni, 2012. "Prince-setting, monetary policy and the contractionary effects of productivity improvements," Departmental Working Papers of Economics - University 'Roma Tre' 0161, Department of Economics - University Roma Tre.
    13. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    14. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    15. Dao, Chi-Mai & Wolters, Jürgen, 2008. "Common stochastic volatility trends in international stock returns," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 431-445, June.
    16. Lettau, Martin & Ludvigson, Sydney, 2001. "Understanding Trend and Cycle in Asset Values: Bulls, Bears and the Wealth Effect on Consumption," CEPR Discussion Papers 3104, C.E.P.R. Discussion Papers.
    17. Martin B. Schmidt, 2004. "Exogeneity within the M2 Demand Function: Evidence from a Large Macroeconomic System," Economic Inquiry, Western Economic Association International, vol. 42(4), pages 634-646, October.
    18. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    19. Martin Schmidt, 2003. "Money and prices: evidence from the G7 countries," Applied Economics, Taylor & Francis Journals, vol. 35(17), pages 1799-1809.
    20. Martin Lettau & Sydney C. Ludvigson & Charles Steindel, 2002. "Monetary policy transmission through the consumption-wealth channel," Economic Policy Review, Federal Reserve Bank of New York, vol. 8(May), pages 117-133.
    21. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.
    22. Martin B. Schmidt, 2000. "The Dynamic Behavior of Wages and Prices: Cointegration Tests within a Large Macroeconomic System," Southern Economic Journal, John Wiley & Sons, vol. 67(1), pages 123-138, July.

  59. F. Javier Fernandez Macho & Andrew C. Harvey & James H. Stock, 1987. "Forecasting and Interpolation Using Vector Autoregressions with Common Trends," Annals of Economics and Statistics, GENES, issue 6-7, pages 279-287.

    Cited by:

    1. Stefan Gerlach & Matthew S. Yiu, 2004. "A Dynamic Factor Model for Current-Quarter Estimates of Economic Activity in Hong Kong," Working Papers 162004, Hong Kong Institute for Monetary Research.
    2. Peter Fuleky & Carl S. Bonham, 2011. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 201110, University of Hawaii at Manoa, Department of Economics.
    3. Juan Carlos Carlo Santos, 2019. "Pronósticos del PIB mediante modelos de factores dinámicos," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 30(1), pages 125-174, January -.
    4. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    5. Francisco J. Goerlich-Gisbert, 1999. "Shocks agregados versus shocks sectoriales. Un análisis factorial dinámico," Investigaciones Economicas, Fundación SEPI, vol. 23(1), pages 27-53, January.
    6. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201305, University of Hawaii at Manoa, Department of Economics.
    7. Fabio H. Nieto, 2007. "Ex post and ex ante prediction of unobserved multivariate time series: a structural-model based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 53-76.
    8. Ko, Byoung Wook, 2010. "An application of dynamic factor model to dry Bulk Market - focusing on the analysis of synchronicity and idiosyncrasy in the sub-markets with different ship - size," MPRA Paper 32572, University Library of Munich, Germany.

  60. Harvey, A. C., 1986. "The effects of seat belt legislation on British road casualities: A case study in structural modelling : A.C. Harvey and J. Durbing, Journal of the Royal Statistical Society, Series A 149 (1986) (in p," International Journal of Forecasting, Elsevier, vol. 2(4), pages 496-497.

    Cited by:

    1. P. A. Scuffham, 2003. "Economic factors and traffic crashes in New Zealand," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 179-188.
    2. Yuehjen Shao & Yue-Fa Lin & Soe-Tsyr Yuan, 1999. "Integrated application of time series multiple-interventions analysis and knowledge-based reasoning," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 755-766.
    3. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    4. OUERFELLI, Chokri, 1998. "La demande touristique européenne en Tunisie," LATEC - Document de travail - Economie (1991-2003) 1998-14, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    5. Mark Hon & Soo-Keong Yong, 2004. "The price of owning a car: an analysis of auction quota premium in Singapore," Applied Economics, Taylor & Francis Journals, vol. 36(7), pages 739-751.
    6. Atkinson, A. C. & Koopman, S. J. & Shephard, N., 1997. "Detecting shocks: Outliers and breaks in time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 387-422, October.
    7. Victor Guerrero, 2005. "Restricted estimation of an adjusted time series: application to Mexico's industrial production index," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(2), pages 157-177.
    8. Naci H. Mocan & Kudret Topyan, 1993. "Illicit Drug Use and Health: Analysis and Projections of New York City Birth Outcomes Using a Kalman Filter Model," NBER Working Papers 4359, National Bureau of Economic Research, Inc.
    9. Manuel Salvador & Pilar Gargallo, 2003. "Automatic selective intervention in dynamic linear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1161-1184.

  61. A. C. Harvey, 1986. "Analysis and Generalisation of a Multivariate Exponential Smoothing Model," Management Science, INFORMS, vol. 32(3), pages 374-380, March.

    Cited by:

    1. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    2. Sbrana, Giacomo & Silvestrini, Andrea, 2020. "Forecasting with the damped trend model using the structural approach," International Journal of Production Economics, Elsevier, vol. 226(C).
    3. Sbrana, Giacomo & Pelagatti, Matteo, 2024. "Optimal hierarchical EWMA forecasting," International Journal of Forecasting, Elsevier, vol. 40(2), pages 616-625.
    4. George Athanasopoulos & Ashton de Silva, 2010. "Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand," Monash Econometrics and Business Statistics Working Papers 11/09, Monash University, Department of Econometrics and Business Statistics.
    5. Stelios Bekiros & Alessia Paccagnini, 2013. "Policy-oriented macroeconomic forecasting with hybrid DGSE and time-varying parameter VAR models," Working Papers 236, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    6. Sbrana, Giacomo & Silvestrini, Andrea, 2023. "The RWDAR model: A novel state-space approach to forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 922-937.
    7. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
    8. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
    9. Mirko Kremer & Enno Siemsen & Douglas J. Thomas, 2016. "The Sum and Its Parts: Judgmental Hierarchical Forecasting," Management Science, INFORMS, vol. 62(9), pages 2745-2764, September.
    10. K. Triantafyllopoulos, 2007. "Covariance estimation for multivariate conditionally Gaussian dynamic linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 551-569.
    11. Bermúdez, José D. & Corberán-Vallet, Ana & Vercher, Enriqueta, 2009. "Multivariate exponential smoothing: A Bayesian forecast approach based on simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1761-1769.
    12. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
    13. Sbrana, Giacomo & Silvestrini, Andrea, 2022. "Random coefficient state-space model: Estimation and performance in M3–M4 competitions," International Journal of Forecasting, Elsevier, vol. 38(1), pages 352-366.
    14. Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2013. "Forecasting multivariate time series with the Theta Method," Working Papers 13004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    15. Croux, Christophe & Gelper, Sarah & Mahieu, Koen, 2010. "Robust exponential smoothing of multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2999-3006, December.
    16. González, Fernando & Launonen, Simo, 2005. "Towards European monetary integration: the evolution of currency risk premium as a measure for monetary convergence prior to the implementation of currency unions," Working Paper Series 569, European Central Bank.
    17. Sbrana, Giacomo & Silvestrini, Andrea, 2019. "Random switching exponential smoothing: A new estimation approach," International Journal of Production Economics, Elsevier, vol. 211(C), pages 211-220.
    18. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.
    19. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    20. Bekiros, Stelios, 2014. "Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area," Economic Modelling, Elsevier, vol. 38(C), pages 619-626.
    21. Triantafyllopoulos, Kostas, 2006. "Multivariate discount weighted regression and local level models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3702-3720, August.

  62. Harvey, A C, et al, 1986. "Stochastic Trends in Dynamic Regression Models: An Application to the Employment-Output Equations," Economic Journal, Royal Economic Society, vol. 96(384), pages 975-985, December.

    Cited by:

    1. Abdul Karim, Zulkefly & Md. Said, Fathin Faezah & Jusoh, Mansor & Md. Thahir, Md. Zyadi, 2009. "Monetary policy and inflation targeting in a small open-economy," MPRA Paper 23949, University Library of Munich, Germany, revised 10 Jan 2010.
    2. Sturla Furunes Kvamsdal, 2019. "Indexing of Technical Change in Aggregated Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 901-920, March.
    3. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    4. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters, in: Lester C. Hunt (ed.), Energy in a Competitive Market, chapter 9, Edward Elgar Publishing.
    5. Yongkyun Chung, 1997. "Labor Hoarding and SRIRL Pardox: Some Evidences from United Kingdom and United States," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 1(1), pages 175-189, December.
    6. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," Stirling Economics Discussion Papers 2014-12, University of Stirling, Division of Economics.
    7. Kapombe, Crispin M. & Colyer, Dale, 1999. "A structural time series analysis of US broiler exports," Agricultural Economics, Blackwell, vol. 21(3), pages 295-307, December.
    8. Gorter, C. & Hassink, W. & Nijkamp, P., 1996. "On the endogeneity of output in dynamic labour-demand models," Serie Research Memoranda 0019, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    9. Richard Dickens & Stephen Machin & Alan Manning & David Metcalf & Jonathan Wadsworth & S Woodland, 1994. "The Effect of Minimum Wages on UK Agriculture," CEP Discussion Papers dp0204, Centre for Economic Performance, LSE.
    10. Everaert Gerdie, 2011. "Estimation and Inference in Time Series with Omitted I(1) Variables," Journal of Time Series Econometrics, De Gruyter, vol. 2(2), pages 1-28, January.
    11. Streibel, Mariane & Harvey, Andrew, 1993. "Estimation of simultaneous equation models with stochastic trend components," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 263-287.
    12. Guro Børnes Ringlund & Knut Einar Rosendahl & Terje Skjerpen, 2004. "Does oilrig activity react to oil price changes? An empirical investigation," Discussion Papers 372, Statistics Norway, Research Department.
    13. Chew Lian Chua & G. C. Lim & Sarantis Tsiaplias, 2012. "A latent variable approach to forecasting the unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(3), pages 229-244, April.
    14. Jaakko Pehkonen, 1994. "Testing weak exogeneity by multivariate cointegration techniques : the demand for labour in Finnish manufacturing," Finnish Economic Papers, Finnish Economic Association, vol. 7(2), pages 108-119, Autumn.
    15. Zafer Dilaver & Lester C Hunt, 2010. "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 129, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    16. Addison, John T. & Teixeira, Paulino, 1999. "Is Portugal really so arteriosclerotic? Results from a cross-country analysis of labor adjustment," ZEW Discussion Papers 99-30, ZEW - Leibniz Centre for European Economic Research.
    17. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    18. Malin Gardberg & Lorenzo Pozzi, 2022. "Aggregate consumption and wealth in the long run: The impact of financial liberalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 161-186, January.
    19. Addison John T. & Teixeira Paulino, 2001. "Employment Adjustment in a “Sclerotic” Labour Market: Comparing Portugal with Germany, Spain, and the United Kingdom / Beschäftigungsanpassung in einem „sklerotischen“ Arbeitsmarkt: Ein Vergleich von ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 221(4), pages 353-370, August.
    20. G. Everaert, 2007. "Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/452, Ghent University, Faculty of Economics and Business Administration.
    21. SHIRANI-FAKHR, Zohreh & KHOSHAKHLAGH, Rahman & SHARIFI, Alimorad, 2015. "Estimating Demand Function For Electricity In Industrial Sector Of Iran Using Structural Time Series Model (Stsm)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(1), pages 143-160.
    22. Chen, Xiaoshan & MacDonald, Ronald, 2010. "Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models," SIRE Discussion Papers 2010-41, Scottish Institute for Research in Economics (SIRE).
    23. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    24. Zafer Dilaver & Lester C Hunt, 2010. "Modelling and Forecasting Turkish Residential Electricity Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 131, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    25. Sa'ad, Suleiman, 2010. "Improved technical efficiency and exogenous factors in transportation demand for energy: An application of structural time series analysis to South Korean data," Energy, Elsevier, vol. 35(7), pages 2745-2751.
    26. Bajpai, Siddharth & Mohanty, Samarendu, 2008. "Impacts of Exchange Rate Volatility on the U.S. Cotton Exports," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6849, Southern Agricultural Economics Association.
    27. Al-Rabbaie, Arqam & Alwaked, Ahmad & Altarawneh, Yaseen, 2009. "Underlying trends in employment-output equation: the case of Jordan," Perspectives of Innovations, Economics and Business (PIEB), Prague Development Center (PRADEC), vol. 3, pages 1-3, December.
    28. Martyn Duffy, 2006. "Tobacco consumption and policy in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1235-1257.
    29. Wollmer, F.J. & Butter, F.A.G. den & Hassink, W.H.J., 1991. "Technical progress, endogenous growth and labour productivity : a survey," Serie Research Memoranda 0075, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    30. Stephen Bazen & Velayoudom Marimoutou, 2000. "Looking for a Needle in a Haystack? A Structural Time Series Model of the Relationship Between Teenage Employment and Minimum Wages in the United States," Econometric Society World Congress 2000 Contributed Papers 0495, Econometric Society.
    31. Rodrigo Fuentes & Marco Morales, 2007. "Measuring TFP: A Latent Variable Approach," Working Papers Central Bank of Chile 419, Central Bank of Chile.
    32. Reneéa Koekemoer, 2001. "Variable Parameter Estimation Of Consumer Price Expectations For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 69(1), pages 1-39, March.
    33. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    34. Colyer, Dale, 2000. "A Comparison Of Annual, Quarterly And Monthly Turkey Export Models," Conference Papers 19106, West Virginia University, Department of Agricultural Resource Economics.
    35. Sturla Furunes Kvamsdal, 2016. "Technical Change as a Stochastic Trend in a Fisheries Model," Marine Resource Economics, University of Chicago Press, vol. 31(4), pages 403-419.
    36. Antoni, 2012. "Monetary policy and inflation targeting in a small open economy," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 4(2), pages 187-198, April.
    37. Malin Gardberg & Lorenzo (L.C.G.) Pozzi, 2018. "Consumption and wealth in the long run: an integrated unobserved component approach," Tinbergen Institute Discussion Papers 18-046/VI, Tinbergen Institute, revised 13 Sep 2018.
    38. Stephen Bazen & Velayoudom Marimoutou, 2002. "Looking for a Needle in a Haystack? A Re‐examination of the Time Series Relationship between Teenage Employment and Minimum Wages in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(supplemen), pages 699-725, December.
    39. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.
    40. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.

  63. Harvey, A. C. & Pereira, Pedro Luiz Valls, 1985. "The estimation of dynamic models with missing observations," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 5(2), November.

    Cited by:

    1. Ito, Nobuyasu, 1993. "Non-equilibrium relaxation and interface energy of the Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 196(4), pages 591-614.

  64. Harvey, A. C. & Stock, James H., 1985. "The Estimation of Higher-Order Continuous Time Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 1(1), pages 97-117, April.

    Cited by:

    1. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    2. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    3. Filardo, Andrew & Lombardi, Marco & Raczko, Marek, 2019. "Measuring financial cycle time," Bank of England working papers 776, Bank of England.
    4. Parra-Alvarez, Juan Carlos & Polattimur, Hamza & Posch, Olaf, 2021. "Risk matters: Breaking certainty equivalence in linear approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    5. Lawrence J. Christiano & Martin S. Eichenbaum, 1986. "A continuous time, general equilibrium, inventory-sales model," Working Papers 304, Federal Reserve Bank of Minneapolis.
    6. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    7. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.
    8. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    9. Andrew W. Lo, 1986. "Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data," NBER Technical Working Papers 0059, National Bureau of Economic Research, Inc.
    10. Lars Peter Hansen & Thomas J. Sargent, 1990. "Recursive Linear Models of Dynamic Economies," NBER Working Papers 3479, National Bureau of Economic Research, Inc.
    11. Ghysels, E. & Jasiak, J., 1994. "Stochastic Volatility and time Deformation: An Application of trading Volume and Leverage Effects," Cahiers de recherche 9403, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    12. Lars Peter Hansen & Jose Alexandre Scheinkman, 1993. "Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes," NBER Technical Working Papers 0141, National Bureau of Economic Research, Inc.
    13. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    14. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    15. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
    16. Hermann Singer, 2003. "Simulated Maximum Likelihood in Nonlinear Continuous-Discrete State Space Models: Importance Sampling by Approximate Smoothing," Computational Statistics, Springer, vol. 18(1), pages 79-106, March.
    17. Roderick McCrorie, J., 2001. "Interpolating exogenous variables in continuous time dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1399-1427, September.
    18. Tucker S. McElroy & Thomas M. Trimbur, 2007. "Continuous time extraction of a nonstationary signal with illustrations in continuous low-pass and band-pass filtering," Finance and Economics Discussion Series 2007-68, Board of Governors of the Federal Reserve System (U.S.).
    19. J. Roderick McCrorie, 2000. "The Likelihood of a Continuous-time Vector Autoregressive Model," Working Papers 419, Queen Mary University of London, School of Economics and Finance.
    20. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    21. Hermann Singer, 2011. "Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 375-413, December.
    22. Comte, F., 1998. "Discrete and continuous time cointegration," Journal of Econometrics, Elsevier, vol. 88(2), pages 207-226, November.
    23. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.
    24. Michael A. Thornton & Marcus J. Chambers, 2013. "Continuous-time autoregressive moving average processes in discrete time: representation and embeddability," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 552-561, September.

  65. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.

    Cited by:

    1. Bashar, Omar H.M.N. & Bhattacharya, Prasad Sankar & Wohar, Mark E., 2017. "The cyclicality of fiscal policy: New evidence from unobserved components approach," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 222-234.
    2. Alexander Dokumentov & Rob J. Hyndman, 2015. "STR: A Seasonal-Trend Decomposition Procedure Based on Regression," Monash Econometrics and Business Statistics Working Papers 13/15, Monash University, Department of Econometrics and Business Statistics.
    3. Athanasios Orphanides & Simon van Norden, 1999. "The reliability of output gap estimates in real time," Finance and Economics Discussion Series 1999-38, Board of Governors of the Federal Reserve System (U.S.).
    4. Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    6. Drakos, Konstantinos & Müller, Cathérine, 2011. "Terrorism risk concern in Europe," Economics Letters, Elsevier, vol. 112(2), pages 195-197, August.
    7. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    8. Guglielmo Maria Caporale & Juncal Cunado & Luis A. Gil-Alana, 2008. "Modelling Long-Run Trends and Cycles in Financial Time Series Data," CESifo Working Paper Series 2330, CESifo.
    9. Victor Zarnowitz, 1987. "The Regularity of Business Cycles," NBER Working Papers 2381, National Bureau of Economic Research, Inc.
    10. Kim, Chang-Jin & Kim, Jaeho, 2013. "The `Pile-up Problem' in Trend-Cycle Decomposition of Real GDP: Classical and Bayesian Perspectives," MPRA Paper 51118, University Library of Munich, Germany.
    11. Alessandra Luati & Tommaso Proietti, 2010. "Hyper‐spherical and elliptical stochastic cycles," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 169-181, May.
    12. Andrew Evans, 2018. "Okun coefficients and participation coefficients by age and gender," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-22, December.
    13. Asea, Patrick K & Reinhart, Carmen M, 1996. "Economic Growth and Economic Consequences of External Shocks in Sub-Saharan Africa: Introduction," Journal of African Economies, Centre for the Study of African Economies, vol. 5(3), pages 1-6, October.
    14. Carmen M. Reinhart & Peter Wickham, 1994. "Commodity Prices: Cyclical Weakness or Secular Decline?," IMF Staff Papers, Palgrave Macmillan, vol. 41(2), pages 175-213, June.
    15. Moolman, Elna, 2004. "A Markov switching regime model of the South African business cycle," Economic Modelling, Elsevier, vol. 21(4), pages 631-646, July.
    16. Giacomo Sbrana, 2010. "The exact linkage between the Beveridge-Nelson decomposition and other permanent-transitory decompositions," Working Papers 10-09, Association Française de Cliométrie (AFC).
    17. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    18. Nelson, Charles R., 1988. "Spurious trend and cycle in the state space decomposition of a time series with a unit root," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 475-488.
    19. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
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    21. Amy Y. Guisinger & Ruben Hernandez-Murillo & Michael T. Owyang & Tara M. Sinclair, 2015. "A State-Level Analysis of Okun's Law," Working Papers 2015-29, Federal Reserve Bank of St. Louis.
    22. Kevin Lee & Kalvinder Shields, 2004. "Business survey forecasts and measurement of output trends in five European economies," Money Macro and Finance (MMF) Research Group Conference 2003 52, Money Macro and Finance Research Group.
    23. Klinger, Sabine & Weber, Enzo, 2019. "GDP-Employment decoupling and the slow-down of productivity growth in Germany," IAB-Discussion Paper 201912, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    24. Richard T. Froyen & Roger N. Waud, 1986. "Real Business Cycles and the Lucas Paradigm," NBER Working Papers 2109, National Bureau of Economic Research, Inc.
    25. James Morley & Charles Nelson & Eric Zivot, 2002. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers UWEC-2002-01, University of Washington, Department of Economics.
    26. Nicholas Sly & Caroline Weber, 2013. "International Fiscal Policy Coordination and GDP Comovement," CESifo Working Paper Series 4358, CESifo.
    27. Fernandes, Mário Correia & Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2023. "Modelling output gaps in the Euro Area with structural breaks: The COVID-19 recession," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1046-1058.
    28. Akdi, Yilmaz & Varlik, Serdar & Berument, M. Hakan, 2020. "Duration of Global Financial Cycles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    29. Olivier Basdevant & Nils Björksten & Özer Karagedikli, 2004. "Estimating a time varying neutral real interest rate for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP 2004/01, Reserve Bank of New Zealand.
    30. Yu-Fan Huang & Sui Luo, 2018. "Potential output and inflation dynamics after the Great Recession," Empirical Economics, Springer, vol. 55(2), pages 495-517, September.
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    21. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    22. Agustín Maravall & Cristophe Planas, 1996. "Estimation Error and the Specification of Unobserved Component Models," Working Papers 9608, Banco de España.
    23. Pollock, D. S. G., 2001. "Methodology for trend estimation," Economic Modelling, Elsevier, vol. 18(1), pages 75-96, January.
    24. Garcia-Ferrer, Antonio & Queralt, Ricardo A., 1998. "Can univariate models forecast turning points in seasonal economic time series?," International Journal of Forecasting, Elsevier, vol. 14(4), pages 433-446, December.
    25. Breitung, Jörg, 1998. "On model based seasonal adjustment procedures," SFB 373 Discussion Papers 1998,12, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    26. Huishu Zhang & Jianrong Wei & Jiping Huang, 2014. "Scaling and Predictability in Stock Markets: A Comparative Study," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-5, March.
    27. J. S. Shonkwiler, 1992. "A Structural Time Series Model Of Nevada Gross Taxable Gaming Revenues," The Review of Regional Studies, Southern Regional Science Association, vol. 22(3), pages 239-249, Winter.
    28. Shah, Muhammad Ibrahim & Kirikkaleli, Dervis & Adedoyin, Festus Fatai, 2021. "Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark," Renewable Energy, Elsevier, vol. 175(C), pages 797-806.
    29. Constantinescu, Mihnea & Nguyen, Anh D.M., 2018. "Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization," Economic Systems, Elsevier, vol. 42(4), pages 649-664.
    30. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
    31. Saligari, G.R. & Snyder, R.D., 1996. "Trends, Lead Times and Forecasting," Monash Econometrics and Business Statistics Working Papers 1/96, Monash University, Department of Econometrics and Business Statistics.
    32. Harry M. Karamujic, 2011. "Comparative Analysis of Australian Residential Mortgage (Home Loan) Interest Rates," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 5(3), pages 311-341, August.
    33. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    34. Shujie Shen & Gang Li & Haiyan Song, 2009. "Effect of Seasonality Treatment on the Forecasting Performance of Tourism Demand Models," Tourism Economics, , vol. 15(4), pages 693-708, December.
    35. Candy Mei Fung Tang & Brian King & Stephen Pratt, 2017. "Predicting hotel occupancies with public data," Tourism Economics, , vol. 23(5), pages 1096-1113, August.
    36. Fanhua Yu & Huibowen Hao & Qingliang Li, 2021. "An Ensemble 3D Convolutional Neural Network for Spatiotemporal Soil Temperature Forecasting," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    37. Quanrui Song & Jianxu Liu & Songsak Sriboonchitta, 2019. "Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
    38. Wright, Brian D. & Williams, Jeffrey C., 1990. "The Behavior of Markets for Storable Commodities," 1990 Conference (34th), February 13-15, 1990, Brisbane, Australia 145482, Australian Agricultural and Resource Economics Society.
    39. Ester Ruiz & Fernando Lorenzo, 1997. "Prediction with univariate time series models: The Iberia case," Documentos de Trabajo (working papers) 0298, Department of Economics - dECON.
    40. Johan Verbeeck & Christel Faes & Thomas Neyens & Niel Hens & Geert Verbeke & Patrick Deboosere & Geert Molenberghs, 2023. "A linear mixed model to estimate COVID‐19‐induced excess mortality," Biometrics, The International Biometric Society, vol. 79(1), pages 417-425, March.
    41. Hotta, Luiz K. & Morettin, Pedro A. & Pereira, Pedro L. Valls, 1992. "The Effect of Overlapping Aggregation on Time Series Models: An Application to the Unemployment Rate in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 12(2), November.
    42. Thury, Gerhard & Witt, Stephen F., 1998. "Forecasting industrial production using structural time series models," Omega, Elsevier, vol. 26(6), pages 751-767, December.
    43. Ardeni, Pier Giorgio & Wright, Brian, 1990. "The long term behavior of commodity prices," Policy Research Working Paper Series 358, The World Bank.
    44. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    45. 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.
    46. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    47. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    48. Maravall, Agustín, 1999. "Short-term and long-term trends, seasonal and the business cycle," DES - Working Papers. Statistics and Econometrics. WS 6291, Universidad Carlos III de Madrid. Departamento de Estadística.
    49. Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Further evidence on forecasting international GNP growth rates using unobserved components transfer function models," Documentos de Trabajo del ICAE 9312, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    50. Chen, Chunhang, 1997. "Robustness properties of some forecasting methods for seasonal time series: A Monte Carlo study," International Journal of Forecasting, Elsevier, vol. 13(2), pages 269-280, June.
    51. Jo C. Vu, 2006. "Effect of Demand Volume on Forecasting Accuracy," Tourism Economics, , vol. 12(2), pages 263-276, June.
    52. Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    53. Maravall, Agustín, 1999. "Seasonal outliers in time series," DES - Working Papers. Statistics and Econometrics. WS 6333, Universidad Carlos III de Madrid. Departamento de Estadística.
    54. Philippe Goulet Coulombe & Maximilian Gobel, 2020. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Papers 2005.02535, arXiv.org, revised Mar 2021.
    55. Valadkhani, Abbas & Costello, Greg & Ratti, Ronald, 2016. "House price cycles in Australia’s four largest capital cities," Economic Analysis and Policy, Elsevier, vol. 52(C), pages 11-22.
    56. Sucharita Ghosh & Donald Lien, 2001. "Forecasting with preliminary data: a comparison of two methods," Applied Economics, Taylor & Francis Journals, vol. 33(6), pages 721-726.
    57. Naci H. Mocan & Kudret Topyan, 1993. "Illicit Drug Use and Health: Analysis and Projections of New York City Birth Outcomes Using a Kalman Filter Model," NBER Working Papers 4359, National Bureau of Economic Research, Inc.
    58. Rasi, Chris-Marie & Viikari, Jan-Markus, 1998. "The time-varying NAIRU and potential output in Finland," Bank of Finland Research Discussion Papers 6/1998, Bank of Finland.
    59. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Working Papers 21-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    60. Pablo Marshall, 1998. "Prediccion De Series De Ventas: Un Analisis De Cointegracion Con El Pib," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 1(1), pages 89-109.
    61. Michael A. Kouparitsas, 1999. "Is there evidence of the new economy in the data?," Working Paper Series WP-99-22, Federal Reserve Bank of Chicago.
    62. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.

  68. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study: Response," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 313-315, October.

    Cited by:

    1. [Reference to Proietti], Tommaso, 2000. "Comparing seasonal components for structural time series models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 247-260.
    2. Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2015. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    3. Guido Ascari & Paolo Bonomolo & Qazi Haque, 2023. "The Long-Run Phillips Curve is ... a Curve," CAMA Working Papers 2023-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Sen Cheong Kon & Lindsay W. Turner, 2005. "Neural Network Forecasting of Tourism Demand," Tourism Economics, , vol. 11(3), pages 301-328, September.
    5. Giacomo Sbrana, 2010. "The exact linkage between the Beveridge-Nelson decomposition and other permanent-transitory decompositions," Working Papers 10-09, Association Française de Cliométrie (AFC).
    6. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Papers 9510, Tilburg - Center for Economic Research.
    7. Nelson, Charles R., 1988. "Spurious trend and cycle in the state space decomposition of a time series with a unit root," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 475-488.
    8. Paolo Maranzano & Alessandro Fassò & Matteo Pelagatti & Manfred Mudelsee, 2020. "Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy," IJERPH, MDPI, vol. 17(3), pages 1-22, February.
    9. Victor Gomez & Jorg Breitung, 1999. "The Beveridge–Nelson Decomposition: A Different Perspective with New Results," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(5), pages 527-535, September.
    10. Paolo Guarda, 2002. "Potential output and the output gap in Luxembourg: some alternative methods," BCL working papers 4, Central Bank of Luxembourg.
    11. Andrés Bujosa Brun & Marcos Bujosa Brun & Antonio García-Ferrer, 2013. "Mathematical framework for pseudo-spectra of linear stochastic difference equations," Documentos de Trabajo del ICAE 2013-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised May 2015.
    12. Constantinescu, Mihnea & Nguyen, Anh Dinh Minh, 2021. "A century of gaps: Untangling business cycles from secular trends," Economic Modelling, Elsevier, vol. 100(C).
    13. Ralf Dewenter & Ulrich Heimeshoff, 2017. "Predicting Advertising Volumes Using Structural Time Series Models: A Case Study," Economics Bulletin, AccessEcon, vol. 37(3), pages 1644-1652.
    14. Stephen Pollock, 2001. "Signal Extraction, Maximum Likelihood Estimation and the Start-up Problem," Working Papers 433, Queen Mary University of London, School of Economics and Finance.
    15. Thornton, Michael A., 2013. "Removing seasonality under a changing regime: Filtering new car sales," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 4-14.
    16. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    17. Bengtsson, Thomas & Cavanaugh, Joseph E., 2006. "An improved Akaike information criterion for state-space model selection," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2635-2654, June.
    18. Mihnea Constantinescu & Anh Dinh Minh Nguyen, 2017. "Unemployment or Credit: Who Holds The Potential? Results From a Small-Open Economy," Bank of Lithuania Discussion Paper Series 4, Bank of Lithuania.
    19. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
    20. Mr. Sebastian Acevedo Mejia & Lu Han & Miss Marie S Kim & Ms. Nicole Laframboise, 2016. "Flying to Paradise: The Role of Airlift in the Caribbean Tourism Industry," IMF Working Papers 2016/033, International Monetary Fund.
    21. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    22. Agustín Maravall & Cristophe Planas, 1996. "Estimation Error and the Specification of Unobserved Component Models," Working Papers 9608, Banco de España.
    23. Pollock, D. S. G., 2001. "Methodology for trend estimation," Economic Modelling, Elsevier, vol. 18(1), pages 75-96, January.
    24. Garcia-Ferrer, Antonio & Queralt, Ricardo A., 1998. "Can univariate models forecast turning points in seasonal economic time series?," International Journal of Forecasting, Elsevier, vol. 14(4), pages 433-446, December.
    25. Huishu Zhang & Jianrong Wei & Jiping Huang, 2014. "Scaling and Predictability in Stock Markets: A Comparative Study," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-5, March.
    26. J. S. Shonkwiler, 1992. "A Structural Time Series Model Of Nevada Gross Taxable Gaming Revenues," The Review of Regional Studies, Southern Regional Science Association, vol. 22(3), pages 239-249, Winter.
    27. Shah, Muhammad Ibrahim & Kirikkaleli, Dervis & Adedoyin, Festus Fatai, 2021. "Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark," Renewable Energy, Elsevier, vol. 175(C), pages 797-806.
    28. Constantinescu, Mihnea & Nguyen, Anh D.M., 2018. "Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization," Economic Systems, Elsevier, vol. 42(4), pages 649-664.
    29. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
    30. Saligari, G.R. & Snyder, R.D., 1996. "Trends, Lead Times and Forecasting," Monash Econometrics and Business Statistics Working Papers 1/96, Monash University, Department of Econometrics and Business Statistics.
    31. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    32. Shujie Shen & Gang Li & Haiyan Song, 2009. "Effect of Seasonality Treatment on the Forecasting Performance of Tourism Demand Models," Tourism Economics, , vol. 15(4), pages 693-708, December.
    33. Candy Mei Fung Tang & Brian King & Stephen Pratt, 2017. "Predicting hotel occupancies with public data," Tourism Economics, , vol. 23(5), pages 1096-1113, August.
    34. Fanhua Yu & Huibowen Hao & Qingliang Li, 2021. "An Ensemble 3D Convolutional Neural Network for Spatiotemporal Soil Temperature Forecasting," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    35. Quanrui Song & Jianxu Liu & Songsak Sriboonchitta, 2019. "Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
    36. Ester Ruiz & Fernando Lorenzo, 1997. "Prediction with univariate time series models: The Iberia case," Documentos de Trabajo (working papers) 0298, Department of Economics - dECON.
    37. Johan Verbeeck & Christel Faes & Thomas Neyens & Niel Hens & Geert Verbeke & Patrick Deboosere & Geert Molenberghs, 2023. "A linear mixed model to estimate COVID‐19‐induced excess mortality," Biometrics, The International Biometric Society, vol. 79(1), pages 417-425, March.
    38. Hotta, Luiz K. & Morettin, Pedro A. & Pereira, Pedro L. Valls, 1992. "The Effect of Overlapping Aggregation on Time Series Models: An Application to the Unemployment Rate in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 12(2), November.
    39. Thury, Gerhard & Witt, Stephen F., 1998. "Forecasting industrial production using structural time series models," Omega, Elsevier, vol. 26(6), pages 751-767, December.
    40. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    41. 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.
    42. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    43. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    44. Maravall, Agustín, 1999. "Short-term and long-term trends, seasonal and the business cycle," DES - Working Papers. Statistics and Econometrics. WS 6291, Universidad Carlos III de Madrid. Departamento de Estadística.
    45. Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Further evidence on forecasting international GNP growth rates using unobserved components transfer function models," Documentos de Trabajo del ICAE 9312, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    46. Chen, Chunhang, 1997. "Robustness properties of some forecasting methods for seasonal time series: A Monte Carlo study," International Journal of Forecasting, Elsevier, vol. 13(2), pages 269-280, June.
    47. Jo C. Vu, 2006. "Effect of Demand Volume on Forecasting Accuracy," Tourism Economics, , vol. 12(2), pages 263-276, June.
    48. Maravall, Agustín, 1999. "Seasonal outliers in time series," DES - Working Papers. Statistics and Econometrics. WS 6333, Universidad Carlos III de Madrid. Departamento de Estadística.
    49. Philippe Goulet Coulombe & Maximilian Gobel, 2020. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Papers 2005.02535, arXiv.org, revised Mar 2021.
    50. Valadkhani, Abbas & Costello, Greg & Ratti, Ronald, 2016. "House price cycles in Australia’s four largest capital cities," Economic Analysis and Policy, Elsevier, vol. 52(C), pages 11-22.
    51. Sucharita Ghosh & Donald Lien, 2001. "Forecasting with preliminary data: a comparison of two methods," Applied Economics, Taylor & Francis Journals, vol. 33(6), pages 721-726.
    52. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    53. Naci H. Mocan & Kudret Topyan, 1993. "Illicit Drug Use and Health: Analysis and Projections of New York City Birth Outcomes Using a Kalman Filter Model," NBER Working Papers 4359, National Bureau of Economic Research, Inc.
    54. Rasi, Chris-Marie & Viikari, Jan-Markus, 1998. "The time-varying NAIRU and potential output in Finland," Bank of Finland Research Discussion Papers 6/1998, Bank of Finland.
    55. Pablo Marshall, 1998. "Prediccion De Series De Ventas: Un Analisis De Cointegracion Con El Pib," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 1(1), pages 89-109.
    56. Michael A. Kouparitsas, 1999. "Is there evidence of the new economy in the data?," Working Paper Series WP-99-22, Federal Reserve Bank of Chicago.
    57. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.

  69. Harvey, Andrew C & Phillips, Garry D A, 1982. "Testing for Contemporaneous Correlation of Disturbances in Systems of Regression Equations," Bulletin of Economic Research, Wiley Blackwell, vol. 34(2), pages 79-91, November.

    Cited by:

    1. Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Exact tests for contemporaneous correlation of disturbances in seemingly unrelated regressions," Journal of Econometrics, Elsevier, vol. 106(1), pages 143-170, January.
    2. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models," Cahiers de recherche 2003-08, Universite de Montreal, Departement de sciences economiques.
    3. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    4. Dufour, Jean-Marie & Khalaf, Lynda, 2001. "Finite-Sample Simulation-Based Tests in Seemingly Unrelated Regressions," Cahiers de recherche 0105, GREEN.
    5. Mitze, Timo & Alecke, Björn & Untiedt, Gerhard, 2009. "Trade-FDI Linkages in a System of Gravity Equations for German Regional Data," Ruhr Economic Papers 84, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    6. Mitze, Timo & Alecke, Björn & Untiedt, Gerhard, 2008. "Trade, FDI and Cross-Variable Linkages: A German (Macro-)Regional Perspective," MPRA Paper 12245, University Library of Munich, Germany.
    7. Tsay, Wen-Jen, 2004. "Testing for contemporaneous correlation of disturbances in seemingly unrelated regressions with serial dependence," Economics Letters, Elsevier, vol. 83(1), pages 69-76, April.

  70. Harvey, A. C. & Phillips, G. D. A., 1981. "Testing for heteroscedasticity in simultaneous equation models," Journal of Econometrics, Elsevier, vol. 15(3), pages 311-340, April.

    Cited by:

    1. Jenkins, Stephen & Austen-Smith, David, 1987. "Interdependent decision-making in non-profit industries: A simultaneous equation analysis of English provincial theatre," International Journal of Industrial Organization, Elsevier, vol. 5(2), pages 149-174.
    2. David E. A. Giles & Peter Hampton, 1985. "An Engel Curve Analysis of Household Expenditure in New Zealand," The Economic Record, The Economic Society of Australia, vol. 61(1), pages 450-462, March.
    3. Song Jiang & Shuang Qiu & Hong Zhou & Meilan Chen, 2019. "Can FinTech Development Curb Agricultural Nonpoint Source Pollution?," IJERPH, MDPI, vol. 16(22), pages 1-22, November.

  71. A. C. Harvey, 1981. "Finite Sample Prediction And Overdifferencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(4), pages 221-232, July.

    Cited by:

    1. Ismael Sanchez & Daniel Pena, 2001. "Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(1), pages 45-66, January.

  72. G. Gardner & A. C. Harvey & G. D. A. Phillips, 1980. "An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive–Moving Average Models by Means of Kaiman Filtering," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(3), pages 311-322, November.

    Cited by:

    1. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.
    2. Guy Melard & Roch Roy & Abdessamad Saidi, 2006. "Exact maximum likelihood estimation of structured or unit root multivariate time series models," ULB Institutional Repository 2013/13754, ULB -- Universite Libre de Bruxelles.
    3. Mauricio, Jose Alberto, 2008. "Computing and using residuals in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1746-1763, January.
    4. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    5. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
    6. Zeng, Zijian & Li, Meng, 2021. "Bayesian median autoregression for robust time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1000-1010.
    7. Harvey, A. C. & Pereira, Pedro Luiz Valls, 1985. "The estimation of dynamic models with missing observations," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 5(2), November.
    8. Sophie Bercu & Fr�d�ric Proïa, 2013. "A SARIMAX coupled modelling applied to individual load curves intraday forecasting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1333-1348, June.
    9. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Sam Strong & Siew Ping Tan, 1991. "The Australian Business Cycle: Its Definition and Existence," The Economic Record, The Economic Society of Australia, vol. 67(2), pages 115-125, June.
    11. Rajae Azrak & Guy Melard, 1998. "The exact quasi-likelihood of time dependent ARMA models," ULB Institutional Repository 2013/13740, ULB -- Universite Libre de Bruxelles.
    12. Che-Yu Hung & Chien-Chih Wang & Shi-Woei Lin & Bernard C. Jiang, 2022. "An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    13. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    14. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
    15. Zijian Zeng & Meng Li, 2020. "Bayesian Median Autoregression for Robust Time Series Forecasting," Papers 2001.01116, arXiv.org, revised Dec 2020.
    16. Rui Pedro Brito & Pedro Alarcão Judice, 2021. "Efficient credit portfolios under IFRS 9," CeBER Working Papers 2021-07, Centre for Business and Economics Research (CeBER), University of Coimbra.
    17. Gao, Meng & Ge, Ruijun, 2024. "Mapping time series into signed networks via horizontal visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    18. Amitava Mukherjee, 2013. "Nonparametric Phase-II monitoring for detecting monotone trend based on inverse sampling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 131-153, June.

  73. Harvey, A C & Phillips, G D A, 1980. "Testing for Serial Correlation in Simultaneous Equation Models," Econometrica, Econometric Society, vol. 48(3), pages 747-759, April.

    Cited by:

    1. Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Exact tests for contemporaneous correlation of disturbances in seemingly unrelated regressions," Journal of Econometrics, Elsevier, vol. 106(1), pages 143-170, January.
    2. Palm, F.C., 1981. "Structural econometric modelling and time series analysis towards an integrated approach," Serie Research Memoranda 0004, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    3. Liu-Evans, Gareth & Phillips, Garry D.A., 2018. "On the use of higher order bias approximations for 2SLS and k-class estimators with non-normal disturbances and many instruments," Econometrics and Statistics, Elsevier, vol. 6(C), pages 90-105.
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  74. Harvey, A C, 1980. "On Comparing Regression Models in Levels and First Differences," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(3), pages 707-720, October.

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    1. Tomasz Wisniewski & Geoffrey Lightfoot & Simon Lilley, 2012. "Speculating on presidential success: exploring the link between the price–earnings ratio and approval ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 106-122, January.
    2. Franc{c}ois Lafond & Aimee Gotway Bailey & Jan David Bakker & Dylan Rebois & Rubina Zadourian & Patrick McSharry & J. Doyne Farmer, 2017. "How well do experience curves predict technological progress? A method for making distributional forecasts," Papers 1703.05979, arXiv.org, revised Sep 2017.
    3. Miyazaki, Shigetaka & Griffiths, William E., 1984. "The properties of some covariance matrix estimators in linear models with AR(1) errors," Economics Letters, Elsevier, vol. 14(4), pages 351-356.
    4. Eva Gutiérrez-i-Puigarnau & Jos N van Ommeren, 2015. "Commuting and labour supply revisited," Urban Studies, Urban Studies Journal Limited, vol. 52(14), pages 2551-2563, November.
    5. Donyina-Ameyaw, Samuel, 2004. "A Small Macroeconmetric Model Of Trade And Inflation In Ghana," The Warwick Economics Research Paper Series (TWERPS) 696, University of Warwick, Department of Economics.
    6. Mahmood, Talat, 1990. "Die Dynamik der Rentabilität als stochastischer Prozess: eine empirische Zeitreihenanalyse von ausgewählten deutschen und amerikanischen Unternehmen. Vom Fachbereich 20 Informatik der Technischen Univ," EconStor Books, ZBW - Leibniz Information Centre for Economics, number 112236, September.
    7. Bennett T. McCallum, 1993. "Unit roots in macroeconomic time series: some critical issues," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 13-44.
    8. Asgeir Danielsson, 2021. "Wages and prices of foreign goods in the inflationary process in Iceland," Economics wp87, Department of Economics, Central bank of Iceland.
    9. Hassan, Aminu & Kouhy, Reza, 2013. "Gas flaring in Nigeria: Analysis of changes in its consequent carbon emission and reporting," Accounting forum, Elsevier, vol. 37(2), pages 124-134.

  75. Harvey, Andrew C, 1978. "Linear Regression in the Frequency Domain," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(2), pages 507-512, June.

    Cited by:

    1. D.M. Nachane & Amlendu Kumar Dubey, 2008. "The vanishing role of money in the macroeconomy: An Empirical investigation based on spectral and wavelet analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2008-022, Indira Gandhi Institute of Development Research, Mumbai, India.
    2. Christoffersson, Jan, 1997. "A resampling method for regression models with serially correlated errors," Computational Statistics & Data Analysis, Elsevier, vol. 25(1), pages 43-53, July.
    3. Emmanuel Anoruo & Vasudeva N. R. Murthy, 2017. "An examination of the REIT return–implied volatility relation: a frequency domain approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(3), pages 581-594, July.
    4. Yohei Yamamoto & Pierre Perron, 2013. "Estimating and testing multiple structural changes in linear models using band spectral regressions," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 400-429, October.
    5. Fredy Gamboa-Estrada, 2023. "The Role of Foreign Investors and Local Agents in the Derivatives Market and their Impact on the Exchange Rate in Colombia: A Wavelet Analysis," IHEID Working Papers 12-2023, Economics Section, The Graduate Institute of International Studies.
    6. Feng Zhu, 2005. "The fragility of the Phillips curve: A bumpy ride in the frequency domain," BIS Working Papers 183, Bank for International Settlements.
    7. Wei Yanfeng, 2013. "The Dynamic Relationships between Oil Prices and the Japanese Economy: A Frequency Domain Analysis," Review of Economics & Finance, Better Advances Press, Canada, vol. 3, pages 57-67, May.
    8. Richard K. Crump & Nikolay Gospodinov & Ignacio Lopez Gaffney, 2024. "A Simple Diagnostic for Time-Series and Panel-Data Regressions," Staff Reports 1132, Federal Reserve Bank of New York.
    9. M. Azimmohseni & M. Khalafi & M. Kordkatuli, 2019. "Time series analysis of covariance based on linear transfer function models," Statistical Inference for Stochastic Processes, Springer, vol. 22(1), pages 1-16, April.
    10. 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.
    11. Fabio Busetti & Michele Caivano, 2017. "Low frequency drivers of the real interest rate: a band spectrum regression approach," Temi di discussione (Economic working papers) 1132, Bank of Italy, Economic Research and International Relations Area.
    12. Monteiro, Paulo Santos, 2008. "Testing Full Consumption Insurance in the Frequency Domain," Economic Research Papers 269910, University of Warwick - Department of Economics.
    13. Bjornson, Bruce & Hong Shik Kim & Lee, Kiseok, 1999. "Low and high frequency macroeconomic forces in asset pricing," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(1), pages 77-100.

  76. Harvey, Andrew C. & Collier, Patrick, 1977. "Testing for functional misspecification in regression analysis," Journal of Econometrics, Elsevier, vol. 6(1), pages 103-119, July.

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    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. EVRARD Olivier & LEJEUNE Bernard & THIRY Bernard, 1994. "COÛT DE LA DISTRIBUTION D'EAU EN WALLONIE ET À BRUXELLES Estimation d'une fonction de coût hdonique," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 65(2), pages 333-360, April.
    3. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.
    4. Severini, Thomas A., 1998. "Some properties of inferences in misspecified linear models," Statistics & Probability Letters, Elsevier, vol. 40(2), pages 149-153, September.
    5. Mounts, Wm. Jr. & Sowell, Clifford, 1995. "A statistical note on possible institutional regimes in budget policy," Journal of Macroeconomics, Elsevier, vol. 17(1), pages 149-160.
    6. Bob Hart & Jim Malley, 1999. "On the Cyclicality and Stability of Real Earnings," Working Papers 1999_13, Business School - Economics, University of Glasgow.
    7. Lampin, Laure B.A. & Nadaud, Franck & Grazi, Fabio & Hourcade, Jean-Charles, 2013. "Long-term fuel demand: Not only a matter of fuel price," Energy Policy, Elsevier, vol. 62(C), pages 780-787.
    8. John F. McDonald & Paul J. Prather, 1994. "Suburban Employment Centres: The Case of Chicago," Urban Studies, Urban Studies Journal Limited, vol. 31(2), pages 201-218, March.
    9. Oguz Ersan & Sagi Akron & Ender Demir, 2019. "The effect of European and global uncertainty on stock returns of travel and leisure companies," Tourism Economics, , vol. 25(1), pages 51-66, February.
    10. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    11. Abu N.M. Wahid & Mohammad Salahuddin & Abdullah M. Noman, 2010. "Savings and investment in South Asia," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 37(6), pages 658-666, November.
    12. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    13. Nigel Meade & Towhidul Islam, 1998. "Technological Forecasting---Model Selection, Model Stability, and Combining Models," Management Science, INFORMS, vol. 44(8), pages 1115-1130, August.
    14. Saralees Nadarajah & Stephen Chan & Emmanuel Afuecheta, 2014. "Extreme value analysis for emerging African markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1347-1360, May.
    15. Kastens, Terry L. & Schroeder, Ted C., 1996. "Efficiency Tests Of July Kansas City Wheat Futures," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 21(2), pages 1-12, December.

  77. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.

    Cited by:

    1. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
    2. Arndt Reichert & Harald Tauchmann, 2014. "When outcome heterogeneously matters for selection: a generalized selection correction estimator," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 762-768, March.
    3. Santos Silva, Joao & Tenreyro, Silvana, 2013. "Trading partners and trading volumes: implementing the Helpman-Melitz-Rubinstein model empirically," LSE Research Online Documents on Economics 55398, London School of Economics and Political Science, LSE Library.
    4. Nguyen, Quyen T.K. & Almodóvar, Paloma, 2018. "Export intensity of foreign subsidiaries of multinational enterprises: The role of trade finance availability," International Business Review, Elsevier, vol. 27(1), pages 231-245.
    5. Buch Claudia M & Doepke Joerg & Stahn Kerstin, 2009. "Great Moderation at the Firm Level? Unconditional vs. Conditional Output Volatility," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 9(1), pages 1-27, May.
    6. Arthur Brooks & Jan Ondrich, 2007. "Quality, service level, or empire: which is the objective of the nonprofit arts firm?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 31(2), pages 129-142, June.
    7. Mukherjee, Sacchidananda & Rao, R. Kavita, 2017. "Determinants of Registration of Unincorporated Enterprises under State Value Added Tax Act in India," MPRA Paper 81236, University Library of Munich, Germany.
    8. Z. L. Yang Y. K. Tse, 2004. "Tests of Functional Form and Heteroscedasticity," Econometric Society 2004 Australasian Meetings 302, Econometric Society.
    9. Spierdijk, L. & Nijman, T.E. & van Soest, A.H.O., 2002. "Modeling Comovements in Trading Intensities to Distinguish Sector and Stock Specific News," Other publications TiSEM 2d40059c-bb27-40ee-b214-a, Tilburg University, School of Economics and Management.
    10. Maria Kyriacou & Peter C.B. Phillips & Francesca Rossi, 2019. "Continuously Updated Indirect Inference in Heteroskedastic Spatial Models," Working Papers 15/2019, University of Verona, Department of Economics.
    11. Daniel Simundza, 2017. "Cream Puffs," Journal of Sports Economics, , vol. 18(8), pages 787-802, December.
    12. Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-04676112, HAL.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian Brownlees & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
      • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
      • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Frömmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
      • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
      • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
      • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüß, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Menac, 2024. "Nonstandard errors," LSE Research Online Documents on Economics 123002, London School of Economics and Political Science, LSE Library.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
      • Ferrara, Gerardo & Jurkatis, Simon, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad‐Díaz & Menachem (Meni) Abudy , 2024. "Nonstandard Errors," Journal of Finance, American Finance Association, vol. 79(3), pages 2339-2390, June.
      • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
      • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
      • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
      • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
      • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
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    17. Howard, Donald D. & English, Burton C. & Larson, James A. & Roberts, Roland K. & Walters, Jeremy T., 2004. "Effects Of Risk, Disease, And Nitrogen Source On Optimal Nitrogen Fertilization Rates In Winter Wheat Production," 2004 Annual Meeting, February 14-18, 2004, Tulsa, Oklahoma 34688, Southern Agricultural Economics Association.
    18. Trevor A. Reeve, 2002. "Factor endowments and industrial structure," International Finance Discussion Papers 731, Board of Governors of the Federal Reserve System (U.S.).
    19. Brown, Sarah & Greene, William H. & Harris, Mark N. & Taylor, Karl, 2015. "An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donations," Economic Modelling, Elsevier, vol. 50(C), pages 228-236.
    20. Stacy, Brian, 2014. "Left with Bias? Quantile Regression with Measurement Error in Left Hand Side Variables," EconStor Preprints 104744, ZBW - Leibniz Information Centre for Economics.
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    27. Justus Haucap & Nima Moshgbar & W. Benedikt Schmal, 2021. "The impact of the German 'DEAL' on competition in the academic publishing market," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(8), pages 2027-2049, December.
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    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. Jan R. Magnus & Ashoke K. Sinha, 2005. "On Theil's errors," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 39-54, March.
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    7. John F. McDonald & Paul J. Prather, 1994. "Suburban Employment Centres: The Case of Chicago," Urban Studies, Urban Studies Journal Limited, vol. 31(2), pages 201-218, March.
    8. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.

Chapters

  1. Harvey, Andrew, 2006. "Forecasting with Unobserved Components Time Series Models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 7, pages 327-412, Elsevier.

    Cited by:

    1. Chen, Yen-Hsiao & Quan, Lianfeng & Liu, Yang, 2013. "An empirical investigation on the temporal properties of China's GDP," China Economic Review, Elsevier, vol. 27(C), pages 69-81.
    2. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," Stirling Economics Discussion Papers 2014-12, University of Stirling, Division of Economics.
    3. Lozinskaia, Agata & Redkina, Anastasiia & Shenkman, Evgeniia, 2020. "Electricity consumption forecasting for integrated power system with seasonal patterns," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 5-25.
    4. Parra-Alvarez, Juan Carlos & Polattimur, Hamza & Posch, Olaf, 2021. "Risk matters: Breaking certainty equivalence in linear approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    5. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    6. Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2007. "Forecasting key macroeconomic variables from a large number of predictors: A state space approach," Discussion Papers 504, Statistics Norway, Research Department.
    7. Arora, Vipin, 2013. "Comparisons of Chinese and Indian Energy Consumption Forecasting Models," MPRA Paper 48621, University Library of Munich, Germany.
    8. 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].
    9. Tsyplakov, Alexander, 2015. "Quasifiltering for time-series modeling," MPRA Paper 66453, University Library of Munich, Germany.
    10. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    11. A. Peyrache & A. N. Rambaldi, 2017. "Incorporating temporal and country heterogeneity in growth accounting—an application to EU-KLEMS," Journal of Productivity Analysis, Springer, vol. 47(2), pages 143-166, April.
    12. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    13. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    14. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, January.
    15. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
    16. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    17. El-Shagi, Makram & Giesen, Sebastian, 2013. "Money and inflation: Consequences of the recent monetary policy," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 520-537.
    18. Chattopadhyay, Siddhartha & Sahu, Sohini & Jha, Saakshi, 2016. "Estimation of Unobserved Inflation Expectations in India using State-Space Model," MPRA Paper 72710, University Library of Munich, Germany.
    19. Kazi Abrar, Hossain & Syed Abul, Basher & A.K. Enamul, Haque, 2017. "Quantifying the impact of Ramadan on global raw sugar prices," MPRA Paper 75941, University Library of Munich, Germany.
    20. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    21. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    22. Giacomo Sbrana & Andrea Silvestrini & Fabrizio Venditti, 2015. "Short term inflation forecasting: the M.E.T.A. approach," Temi di discussione (Economic working papers) 1016, Bank of Italy, Economic Research and International Relations Area.
    23. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    24. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    25. Kazi Abrar Hossain & Syed Abul Basher & A.K. Enamul Haque, 2018. "Quantifying the impact of Ramadan on global raw sugar prices," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 11(4), pages 510-528, June.
    26. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    27. Sbrana, Giacomo & Silvestrini, Andrea, 2014. "Random switching exponential smoothing and inventory forecasting," International Journal of Production Economics, Elsevier, vol. 156(C), pages 283-294.
    28. 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.
    29. Marcin Bartkowiak, 2018. "Mortality modelling. Model specification and mortality forecast accuracy," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 51, pages 13-36.
    30. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    31. Aye, Goodness C. & Balcilar, Mehmet & Gupta, Rangan & Majumdar, Anandamayee, 2015. "Forecasting aggregate retail sales: The case of South Africa," International Journal of Production Economics, Elsevier, vol. 160(C), pages 66-79.
    32. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    33. Ian Dew-Becker, 2022. "Real-Time Forward-Looking Skewness over the Business Cycle," NBER Working Papers 30478, National Bureau of Economic Research, Inc.
    34. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Data Science Solutions for Retail Strategy to Reduce Waste Keeping High Profit," Sustainability, MDPI, vol. 11(13), pages 1-30, June.
    35. Buncic, Daniel, 2020. "Econometric issues with Laubach and Williams’ estimates of the natural rate of interest," Working Paper Series 397, Sveriges Riksbank (Central Bank of Sweden).
    36. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
    37. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Tracking Poisson Parameter for Non-Stationary Discontinuous Time Series with Taylor’s Abnormal Fluctuation Scaling," Stats, MDPI, vol. 2(1), pages 1-15, January.
    38. 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.
    39. Branimir Jovanovic & Magdalena Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," Working Papers 2010-02, National Bank of the Republic of North Macedonia, revised Aug 2010.
    40. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    41. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.
    42. Abhimanyu Dadu & Namrata Gulati, 2014. "Inequality, neighborhoods and variation in prices," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2014-001, Indira Gandhi Institute of Development Research, Mumbai, India.
    43. Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
    44. Søren Johansen & Morten Nyboe Tabor, 2017. "Cointegration between Trends and Their Estimators in State Space Models and Cointegrated Vector Autoregressive Models," Econometrics, MDPI, vol. 5(3), pages 1-15, August.
    45. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    46. Tóth, Máté, 2021. "A multivariate unobserved components model to estimate potential output in the euro area: a production function based approach," Working Paper Series 2523, European Central Bank.
    47. Mardi Dungey & Jan P. A. M. Jacobs & Jing Tian & Simon van Norden, 2013. "Trend-cycle decomposition: implications from an exact structural identification," Working Papers 13-22, Federal Reserve Bank of Philadelphia.
    48. Danica Unevska-Andonova, 2018. "Inflation Decomposition Model: Application to Macedonian inflation," Working Papers 2018-06, National Bank of the Republic of North Macedonia.
    49. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    50. El-Shagi, Makram & Giesen, Sebastian, 2010. "Money and Inflation: The Role of Persistent Velocity Movements," IWH Discussion Papers 2/2010, Halle Institute for Economic Research (IWH).
    51. Katharina Hampel & Marcus Kunz & Norbert Schanne & Ruediger Wapler & Antje Weyh, 2006. "Regional Unemployment Forecasting Using Structural Component Models With Spatial Autocorrelation," ERSA conference papers ersa06p196, European Regional Science Association.
    52. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    53. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.

  2. Andrew C. Harvey, 2002. "Trends, Cycles, and Convergence," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.),Economic Growth: Sources, Trends, and Cycles, edition 1, volume 6, chapter 8, pages 221-250, Central Bank of Chile.
    See citations under working paper version above.

Books

  1. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, January.

    Cited by:

    1. Matkovskyy, Roman & Jalan, Akanksha & Dowling, Michael, 2020. "Effects of economic policy uncertainty shocks on the interdependence between Bitcoin and traditional financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 150-155.
    2. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    3. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
    4. Doan, Bao & Papageorgiou, Nicolas & Reeves, Jonathan J. & Sherris, Michael, 2018. "Portfolio management with targeted constant market volatility," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 134-147.
    5. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    6. Mauro Bernardi & Leopoldo Catania, 2014. "The Model Confidence Set package for R," Papers 1410.8504, arXiv.org.
    7. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    8. Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2015. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    9. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    10. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    11. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    12. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    13. Chen, Cathy Yi-Hsuan & Hafner, Christian, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," LIDAM Reprints ISBA 2019053, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    15. Pawel Janus & Siem Jan Koopman & André Lucas, 2011. "Long Memory Dynamics for Multivariate Dependence under Heavy Tails," Tinbergen Institute Discussion Papers 11-175/2/DSF28, Tinbergen Institute.
    16. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    17. Hafner, Christian M. & Herwartz, Helmut, 2022. "Dynamic score driven independent component analysis," LIDAM Reprints ISBA 2022010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    18. Nguyen, Hoang & Nguyen, Trong-Nghia & Tran, Minh-Ngoc, 2021. "A dynamic leverage stochastic volatility model," Working Papers 2021:14, Örebro University, School of Business.
    19. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    20. Saverio Ranciati & Alberto Roverato & Alessandra Luati, 2021. "Fused graphical lasso for brain networks with symmetries," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1299-1322, November.
    21. Forbes, Kevin F. & Zampelli, Ernest M., 2019. "Wind energy, the price of carbon allowances, and CO2 emissions: Evidence from Ireland," Energy Policy, Elsevier, vol. 133(C).
    22. Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2021. "Modeling and forecasting macroeconomic downside risk," Temi di discussione (Economic working papers) 1324, Bank of Italy, Economic Research and International Relations Area.
    23. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    24. Serge Darolles & Christian Francq & Sébastien Laurent, 2017. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590471, HAL.
    25. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    26. Francq, Christian & Sucarrat, Genaro, 2013. "An Exponential Chi-Squared QMLE for Log-GARCH Models Via the ARMA Representation," MPRA Paper 51783, University Library of Munich, Germany.
    27. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    28. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    29. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    30. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    31. Blazsek, Szabolcs, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    32. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    33. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    34. Z. Sun & P. A. Hamill & Y. Li & Y. C. Yang & S. A. Vigne, 2019. "Did long-memory of liquidity signal the European sovereign debt crisis?," Annals of Operations Research, Springer, vol. 282(1), pages 355-377, November.
    35. Szabolcs Blazsek & William M. Dos Santos & Andreco S. Edwards, 2024. "Score-Driven Interactions for “Disease X” Using COVID and Non-COVID Mortality," Econometrics, MDPI, vol. 12(3), pages 1-24, September.
    36. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    37. Caballero, Diego & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2019. "Risk endogeneity at the lender/investor-of-last-resort," Working Paper Series 2225, European Central Bank.
    38. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    39. Fung, Kennard & Jeong, Jiin & Pereira, Javier, 2022. "More to cryptos than bitcoin: A GARCH modelling of heterogeneous cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PA).
    40. Fernanda Maria Müller & Fábio M Bayer, 2017. "Improved two-component tests in Beta-Skew-t-EGARCH models," Economics Bulletin, AccessEcon, vol. 37(4), pages 2364-2373.
    41. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    42. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    43. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    44. Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2017. "A Justification of Conditional Confidence Intervals," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
    45. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    46. Blazsek, Szabolcs & Licht, Adrian, 2020. "Prediction accuracy of bivariate score-driven risk premium and volatility filters: an illustration for the Dow Jones," UC3M Working papers. Economics 31339, Universidad Carlos III de Madrid. Departamento de Economía.
    47. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    48. Jos'e Vin'icius de Miranda Cardoso & Jiaxi Ying & Daniel Perez Palomar, 2020. "Algorithms for Learning Graphs in Financial Markets," Papers 2012.15410, arXiv.org.
    49. Tsyplakov, Alexander, 2015. "Quasifiltering for time-series modeling," MPRA Paper 66453, University Library of Munich, Germany.
    50. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    51. Kazeem Abimbola Sanusi & Zandri Dickason-Koekemoer, 2022. "Cryptocurrency Returns, Cybercrime and Stock Market Volatility: GAS and Regime Switching Approaches," International Journal of Economics and Financial Issues, Econjournals, vol. 12(6), pages 52-64, November.
    52. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    53. Irving Arturo De Lira Salvatierra & Andrew J. Patton, 2013. "Dynamic Copula Models and High Frequency Data," Working Papers 13-28, Duke University, Department of Economics.
    54. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    55. Lucas, André & Zhang, Xin, 2015. "Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting," Working Paper Series 309, Sveriges Riksbank (Central Bank of Sweden).
    56. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    57. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    58. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    59. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    60. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
    61. 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.
    62. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    63. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    64. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
    65. van Os, Bram & van Dijk, Dick, 2024. "Accelerating peak dating in a dynamic factor Markov-switching model," International Journal of Forecasting, Elsevier, vol. 40(1), pages 313-323.
    66. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    67. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Bounds for Time-Varying Parameters of Observation Driven Models," Tinbergen Institute Discussion Papers 15-027/III, Tinbergen Institute, revised 07 Sep 2015.
    68. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    69. Francq, Christian & Zakoian, Jean-Michel, 2023. "Local Asymptotic Normality Of General Conditionally Heteroskedastic And Score-Driven Time-Series Models," Econometric Theory, Cambridge University Press, vol. 39(5), pages 1067-1092, October.
    70. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    71. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    72. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
    73. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    74. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    75. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    76. Leopoldo Catania & Anna Gloria Billé, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," CEIS Research Paper 375, Tor Vergata University, CEIS, revised 31 Mar 2016.
    77. Gang Cheng & Sicong Wang & Yuhong Yang, 2015. "Forecast Combination under Heavy-Tailed Errors," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    78. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    79. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    80. M. Caivano & A. Harvey, 2013. "Time series models with an EGB2 conditional distribution," Cambridge Working Papers in Economics 1325, Faculty of Economics, University of Cambridge.
    81. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    82. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    83. Blazsek, Szabolcs & Licht, Adrian, 2017. "Score-driven non-linear multivariate dynamic location models," UC3M Working papers. Economics 25739, Universidad Carlos III de Madrid. Departamento de Economía.
    84. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    85. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    86. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    87. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    88. Ángel López-Oriona & José A. Vilar, 2021. "F4: An All-Purpose Tool for Multivariate Time Series Classification," Mathematics, MDPI, vol. 9(23), pages 1-26, November.
    89. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    90. Andrew Harvey & Stephen Thiele, 2014. "Testing against Changing Correlation," Cambridge Working Papers in Economics 1439, Faculty of Economics, University of Cambridge.
    91. Matteo Foglia & Eliana Angelini, 2019. "The Time-Spatial Dimension of Eurozone Banking Systemic Risk," Risks, MDPI, vol. 7(3), pages 1-25, July.
    92. Storti, Giuseppe & Wang, Chao, 2022. "Nonparametric expected shortfall forecasting incorporating weighted quantiles," International Journal of Forecasting, Elsevier, vol. 38(1), pages 224-239.
    93. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    94. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
    95. 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.
    96. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    97. Francesco Calvori & Drew Creal & Siem Jan Koopman & André Lucas, 2017. "Testing for Parameter Instability across Different Modeling Frameworks," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 223-246.
    98. Aknouche, Abdelhakim & Francq, Christian, 2020. "Stationarity and ergodicity of Markov switching positive conditional mean models," MPRA Paper 102503, University Library of Munich, Germany.
    99. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    100. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
    101. Hannes Böhm & Julia Schaumburg & Lena Tonzer, 2022. "Financial Linkages and Sectoral Business Cycle Synchronization: Evidence from Europe," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(4), pages 698-734, December.
    102. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    103. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    104. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    105. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    106. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    107. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    108. 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.
    109. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    110. Mohamed El Ghourabi & Asma Nani & Imed Gammoudi, 2021. "A value‐at‐risk computation based on heavy‐tailed distribution for dynamic conditional score models," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2790-2799, April.
    111. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    112. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    113. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    114. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    115. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    116. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
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    118. Francq, Christian & Zakoian, Jean-Michel, 2024. "Finite moments testing in a general class of nonlinear time series models," MPRA Paper 121193, University Library of Munich, Germany.
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    251. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
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    253. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    254. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    255. F. Blasques & P. Gorgi & S. J. Koopman & J. Sampi, 2023. "Does trade integration imply growth in Latin America? Evidence from a dynamic spatial spillover model," Tinbergen Institute Discussion Papers 23-007/IVI, Tinbergen Institute.
    256. Andrea Guizzardi & Luca Vincenzo Ballestra & Enzo D’Innocenzo, 2024. "Reverse engineering the last-minute on-line pricing practices: an application to hotels," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 943-971, July.
    257. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.
    258. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.

  2. Harvey, Andrew & Proietti, Tommaso (ed.), 2005. "Readings in Unobserved Components Models," OUP Catalogue, Oxford University Press, number 9780199278695.

    Cited by:

    1. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
    2. Proietti, Tommaso & Riani, Marco, 2007. "Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies," MPRA Paper 7862, University Library of Munich, Germany.
    3. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    4. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    5. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
    6. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    7. Tommaso Proietti & Marco Riani, 2009. "Transformations and seasonal adjustment," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 47-69, January.
    8. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    9. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2015. "Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach," CREATES Research Papers 2015-30, Department of Economics and Business Economics, Aarhus University.
    10. Cunha, André Moreira & Lélis, Marcos Tadeo Caputi & Prates, Daniela Magalhães, 2009. "Exchange-rate management in Brazil," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    11. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    12. Javid, Muhammad & Qayyum, Abdul, 2014. "Electricity consumption-GDP nexus in Pakistan: A structural time series analysis," Energy, Elsevier, vol. 64(C), pages 811-817.
    13. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    14. Tommaso Proietti, 2009. "Structural Time Series Models for Business Cycle Analysis," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 9, pages 385-433, Palgrave Macmillan.
    15. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    16. Vitor Leone, 2011. "From Property Companies to Real Estate Investment Trusts: The Impact of Economic and Property Factors on UK Listed Property Returns," Economic Issues Journal Articles, Economic Issues, vol. 16(1), pages 19-36, March.
    17. Jingjing Lyu & Bernd Süssmuth, 2024. "Global Linkages across Sectors and Frequency Bands: A Band Spectral Panel Regression Approach," CESifo Working Paper Series 10970, CESifo.
    18. Dissanayake, G.S. & Peiris, M.S. & Proietti, T., 2016. "State space modeling of Gegenbauer processes with long memory," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 115-130.
    19. Schreiber, Sven, 2014. "The estimation uncertainty of permanent-transitory decompositions in co-integrated systems," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100582, Verein für Socialpolitik / German Economic Association.
    20. Cesar Rodrigues van der Laan & André Moreira Cunha & Marcos Tadeu Caputi Lélis, 2017. "On the effectiveness of capital controls during the Great Recession: The Brazilian experience (2007–2013)," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 40(2), pages 203-222, April.
    21. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    22. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2009. "Survey Data as Coicident or Leading Indicators," Economics Working Papers ECO2009/19, European University Institute.
    23. Zafer Dilaver & Lester C Hunt, 2010. "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 129, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    24. 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.
    25. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, Department of Economics and Business Economics, Aarhus University.
    26. Grassi, Stefano & Santucci de Magistris, Paolo, 2014. "When long memory meets the Kalman filter: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 301-319.
    27. Peter R. Hansen & Asger Lunde, 2010. "Estimating the Persistence and the Autocorrelation Function of a Time Series that is Measured with Error," CREATES Research Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
    28. Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
    29. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    30. Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.
    31. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.

  3. Andrew Harvey (ed.), 1994. "Time Series," Books, Edward Elgar Publishing, volume 0, number 599.

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    1. Afonso Gonçalves da Silva & Peter M Robinson, 2007. "Fractional Cointegration In StochasticVolatility Models," STICERD - Econometrics Paper Series 519, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Daniel Levy, 2000. "Investment–Saving Comovement and Capital Mobility: Evidence from Century Long U.S. Time Series," Post-Print hal-02385594, HAL.
    3. Fabrizio Iacone & Peter M Robinson, 2004. "Cointegration in Fractional Systems with Deterministic Trends," STICERD - Econometrics Paper Series 476, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
    5. Robinson, Peter M. & Henry, Marc, 2003. "Higher-order kernel semiparametric M-estimation of long memory," Journal of Econometrics, Elsevier, vol. 114(1), pages 1-27, May.
    6. Hidalgo, Javier & Robinson, Peter M., 1996. "Testing for structural change in a long-memory environment," Journal of Econometrics, Elsevier, vol. 70(1), pages 159-174, January.
    7. Hualde, J. & Robinson, P.M., 2010. "Semiparametric inference in multivariate fractionally cointegrated systems," Journal of Econometrics, Elsevier, vol. 157(2), pages 492-511, August.
    8. Robinson, Peter M., 2004. "Robust covariance matrix estimation : HAC estimates with long memory/antipersistence correction," LSE Research Online Documents on Economics 2157, London School of Economics and Political Science, LSE Library.
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    12. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
    13. D. Marinucci & P. M. Robinson, 2001. "Finite sample improvements in statistical inference with I(1) processes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 431-444.
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    18. James D. Hamilton & Seth Pruitt & Scott Borger, 2010. "Estimating the Market-Perceived Monetary Policy Rule," NBER Working Papers 16412, National Bureau of Economic Research, Inc.
    19. James D. Hamilton, 2008. "Understanding Crude Oil Prices," NBER Working Papers 14492, National Bureau of Economic Research, Inc.
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    26. Hamilton, James D., 2008. "Daily monetary policy shocks and new home sales," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1171-1190, October.
    27. Hamilton, James D. & Wu, Jing Cynthia, 2014. "Testable implications of affine term structure models," Journal of Econometrics, Elsevier, vol. 178(P2), pages 231-242.
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    29. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 935-947, November.
    30. Thierry Chauveau & Sylvain Friederich & Jérôme Héricourt & Emmanuel Jurczenko & Catherine Lubochinsky & Bertrand Maillet & Christophe Moussu & Bogdan Négréa & Hélène Raymond Feingold, 2004. "La volatilité des marchés augmente-elle ?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00308982, HAL.
    31. Yusuf, Shahid & Nabeshima, Kaoru & Wei Ha, 2007. "What makes cities healthy ?," Policy Research Working Paper Series 4107, The World Bank.
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    33. Atkinson, A. C. & Koopman, S. J. & Shephard, N., 1997. "Detecting shocks: Outliers and breaks in time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 387-422, October.
    34. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
    35. Robinson, Peter M. & Gerolimetto, M., 2006. "Instrumental variables estimation of stationary and nonstationary cointegrating regressions," LSE Research Online Documents on Economics 4539, London School of Economics and Political Science, LSE Library.
    36. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    37. Sean Becketti, 1994. "STB office moving," Stata Technical Bulletin, StataCorp LP, vol. 3(18).
    38. U. Ozlale & E. Yeldan, 2004. "Measuring exchange rate misalignment in Turkey," Applied Economics, Taylor & Francis Journals, vol. 36(16), pages 1839-1849.
    39. Mr. Mardi Dungey & Ms. Renee Fry & Mr. Vance Martin & Ms. Brenda Gonzalez-Hermosillo, 2004. "Empirical Modeling of Contagion: A Review of Methodologies," IMF Working Papers 2004/078, International Monetary Fund.
    40. James D. Hamilton, 2010. "Calling Recessions in Real Time," NBER Working Papers 16162, National Bureau of Economic Research, Inc.
    41. Marinucci, D. & Robinson, Peter M., 2001. "Narrow-band analysis of nonstationary processes," LSE Research Online Documents on Economics 303, London School of Economics and Political Science, LSE Library.
    42. Koichi Maekawa & Sangyeol & Lee, 2004. "The Cusum Test for Parameter Change in Regression with ARCH Errors," Econometric Society 2004 Far Eastern Meetings 606, Econometric Society.
    43. Hamilton, James D. & Wu, Jing Cynthia, 2014. "Risk premia in crude oil futures prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 9-37.
    44. Sean Becketti, 1994. "A library of time series programs for Stata (Update)," Stata Technical Bulletin, StataCorp LP, vol. 3(18).
    45. Giraitis, Liudas & Robinson, Peter M. & Surgailis, Donatas, 1999. "Variance-type estimation of long memory," Stochastic Processes and their Applications, Elsevier, vol. 80(1), pages 1-24, March.
    46. Robinson, Peter M., 2007. "Multiple local whittle estimation in stationary systems," LSE Research Online Documents on Economics 4436, London School of Economics and Political Science, LSE Library.
    47. Lobato, I. & Robinson, P. M., 1996. "Averaged periodogram estimation of long memory," Journal of Econometrics, Elsevier, vol. 73(1), pages 303-324, July.
    48. James D. Hamilton, 2007. "Assessing Monetary Policy Effects Using Daily Fed Funds Futures Contracts," NBER Working Papers 13569, National Bureau of Economic Research, Inc.
    49. Carbon, Michel & Garel, Bernard & Tran, Lanh Tat, 1997. "Frequency polygons for weakly dependent processes," Statistics & Probability Letters, Elsevier, vol. 33(1), pages 1-13, April.
    50. Robinson, P. M., 2001. "The memory of stochastic volatility models," Journal of Econometrics, Elsevier, vol. 101(2), pages 195-218, April.
    51. Catherine Kyrtsou & Michel Terraza, 2000. "Is It Possible To Study Jointly Chaotic And Arch Behaviour? Application Of A Noisy Mackey-Glass Equation With Heteroskedastic Errors To The Paris Stock Exchange," Computing in Economics and Finance 2000 Z226, Society for Computational Economics.
    52. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
    53. Ange Nsouadi & Jules Sadefo Kamdem & Michel Terraza, 2013. "Analyse temps-fréquence de la relation entre les prix du quota et du crédit carbone," Working Papers 13-12, LAMETA, Universtiy of Montpellier, revised Nov 2013.
    54. Young Truong & Prakash Patil, 2001. "Asymptotics for Wavelet Based Estimates of Piecewise Smooth Regression for Stationary Time Series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 159-178, March.
    55. Mohamed A. Ismail & Husni A. Charif, 2003. "Bayesian inference for threshold moving average models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 119-132.
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    1. Alexander Dokumentov & Rob J. Hyndman, 2015. "STR: A Seasonal-Trend Decomposition Procedure Based on Regression," Monash Econometrics and Business Statistics Working Papers 13/15, Monash University, Department of Econometrics and Business Statistics.
    2. Olga Korotkikh, 2020. "A Multi-Country BVAR Model for the External Sector," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 98-112, December.
    3. Ralph D Snyder, 2005. "A Pedant's Approach to Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 5/05, Monash University, Department of Econometrics and Business Statistics.
    4. Syntetos, A.A. & Teunter, R.H., 2014. "On the calculation of safety stocks," Research Report 14003-OPERA, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    5. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    6. Hans Dewachter & Leonardo Iania & Marco Lyrio, 2014. "Information in the yield curve: A Macro-Finance approach," Working Paper Research 254, National Bank of Belgium.
    7. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
    8. Shang, Han Lin & Hyndman, Rob.J., 2011. "Nonparametric time series forecasting with dynamic updating," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1310-1324.
    9. Markus Leippold & Hanlin Yang, 2023. "Mixed‐frequency predictive regressions with parameter learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1955-1972, December.
    10. Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
    11. Yusuf Soner Baskaya & Tugrul Gurgur & Fethi Ogunc, 2008. "Islenmis Gida Fiyatlarini Belirleyen Faktorler," Working Papers 0809, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    12. Ahmed Belhadjayed & Grégoire Loeper & Frédéric Abergel, 2016. "Forecasting Trends With Asset Prices," Post-Print hal-01512431, HAL.
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    14. Chen, Qi-an & Li, Huashi, 2023. "How does exchange rate elasticity of aggregate consumption adjust currency risk price in the stock market?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 590-610.
    15. Dewachter, Hans & Iania, Leonardo, 2012. "An Extended Macro-Finance Model with Financial Factors," LIDAM Reprints LFIN 2012001, Université catholique de Louvain, Louvain Finance (LFIN).
    16. Robert A. Hill & Paulo M. M. Rodrigues, 2022. "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1356-1371, November.
    17. Azumah Karim & Ananda Omotukoh Kube & Bashiru Imoro Ibn Saeed, 2020. "Modeling of Monthly Meteorological Time Series," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-8.
    18. Martha Misas Arango & Enrique López Enciso, 1998. "El Producto Potencial En Colombia: Una Estimación Bajo Var Estructural," Borradores de Economia 2538, Banco de la Republica.
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    20. Álvaro Cartea & Dimitrios Karyampas, 2009. "Volatility and Covariation of Financial Assets: A High-Frequency Analysis," Birkbeck Working Papers in Economics and Finance 0913, Birkbeck, Department of Economics, Mathematics & Statistics.
    21. D.S. Prasada Rao & Alicia Rambaldi & Howard Doran, 2008. "A Method to Construct World Tables of Purchasing Power Parities and Real Incomes Based on Multiple Benchmarks and Auxiliary Information: Analytical and Empirical Results," CEPA Working Papers Series WP052008, School of Economics, University of Queensland, Australia.
    22. Andrés González & Franz Hamann, 2011. "Lack of Credibility, Inflation Persistence and Disinflation in Colombia," Borradores de Economia 658, Banco de la Republica de Colombia.
    23. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    24. Esteban González, María Victoria & Orbe Mandaluniz, Susan, 2006. "Nonparametric estimation betas in the Market Model," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
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    30. Goldstone, Jack A. (Голдстоун, Джек) & Shulgin, Sergey (Шульгин, Сергей) & Arkhangelskiy, Vladimir (Архангельский, Владимир) & Korotaev, Andrey (Коротаев, Андрей) & Zinkina, Yulia (Зинкина, Юлия) & No, 2015. "Political Demography of Russia. Politics and State Government [Политическая Демография России. Политика И Государственное Управление]," Published Papers mn44, Russian Presidential Academy of National Economy and Public Administration.
    31. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
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