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The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series

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  • Dick van Dijk 1
  • Birgit Strikholm
  • Timo Teräsvirta

Abstract

Changes in the seasonal patterns of macroeconomic time series may be due to the effects of business cycle fluctuations or to technological and institutional change or both. We examine the relative importance of these two sources of change in seasonality for quarterly industrial production series of the G7 countries using time-varying smooth transition autoregressive models. We find compelling evidence that the effects of gradual institutional and technological change are much more important than the effects attributable to the business cycle. Copyright Royal Economic Society, 2003

Suggested Citation

  • Dick van Dijk 1 & Birgit Strikholm & Timo Teräsvirta, 2003. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 79-98, June.
    • Handle: RePEc:ect:emjrnl:v:6:y:2003:i:1:p:79-98
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    Cited by:

    1. Siem Jan Koopman & Kai Ming Lee, 2009. "Seasonality with trend and cycle interactions in unobserved components models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 427-448, September.
    2. Craig, Lee & Holt, Matthew T., 2012. "The Role of Mechanical Refrigeration in Spatial and Temporal Price Dynamics for Regional U.S. Egg Markets, 1880–1911," MPRA Paper 39554, University Library of Munich, Germany.
    3. Michael Funke & Marc Gronwald, 2008. "The Undisclosed Renminbi Basket: Are the Markets Telling Us Something about Where the Renminbi–US Dollar Exchange Rate is Going?," The World Economy, Wiley Blackwell, vol. 31(12), pages 1581-1598, December.
    4. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
    5. Gnidchenko, Andrey, 2011. "Моделирование Технологических И Институциональных Эффектов В Макроэкономическом Прогнозировании
      [Technological and Institutional Effects Modeling in Macroeconomic Forecasting]      ," MPRA Paper 35484, University Library of Munich, Germany, revised May 2011.
    6. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, December.
    7. B. Candelon & A. Dupuy & L. Gil-Alana, 2009. "The nature of occupational unemployment rates in the United States: hysteresis or structural?," Applied Economics, Taylor & Francis Journals, vol. 41(19), pages 2483-2493.
    8. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    9. Matas-Mir, Antonio & Osborn, Denise R., 2004. "Does seasonality change over the business cycle? An investigation using monthly industrial production series," European Economic Review, Elsevier, vol. 48(6), pages 1309-1332, December.
    10. Martelotte Marcela Cohen & Souza Reinaldo Castro & Silva Eduardo Antônio Barros da, 2017. "Design of Seasonal Adjustment Filter Robust to Variations in the Seasonal Behaviour of Time Series," Journal of Official Statistics, Sciendo, vol. 33(1), pages 155-186, March.
    11. 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.
    12. Craig, Lee A. & Holt, Matthew T., 2008. "Mechanical refrigeration, seasonality, and the hog-corn cycle in the United States: 1870-1940," Explorations in Economic History, Elsevier, vol. 45(1), pages 30-50, January.
    13. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.
    14. Walter Enders & Matthew T. Holt, 2014. "The Evolving Relationships between Agricultural and Energy Commodity Prices: A Shifting-Mean Vector Autoregressive Analysis," NBER Chapters, in: The Economics of Food Price Volatility, pages 135-187, National Bureau of Economic Research, Inc.
    15. Franses, Philip Hans & van Dijk, Dick, 2005. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," International Journal of Forecasting, Elsevier, vol. 21(1), pages 87-102.
    16. D R Osborn & A Matas-Mir, 2003. "The Extent of Seasonal/Business Cycle Interactions in European Industrial Production," Centre for Growth and Business Cycle Research Discussion Paper Series 38, Economics, The Univeristy of Manchester.
    17. Lokendra Kumawat, 2010. "Modelling changes in seasonality in Indian manufacturing production: an application of the STAR model," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 13(4), pages 361-372.
    18. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    19. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2006. "Não Linearidade Nos Ciclos De Negócios: Modelo Auto-Regressivo “Smooth Transition” Para O Índice Geral De Produção Industrial Brasileiro E Bens De Capital," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 10, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    20. Kumawat, Lokendra, 2010. "Effect of Rainfall on Seasonals in Indian Manufacturing Production: Evidence from Sectoral Data," MPRA Paper 25300, University Library of Munich, Germany.
    21. Dalu Zhang & Peter Moffatt, 2013. "Time series non-linearity in the real growth / recession-term spread relationship," University of East Anglia Applied and Financial Economics Working Paper Series 047, School of Economics, University of East Anglia, Norwich, UK..
    22. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2008. "Modelo de Crescimento Baseado nas Exportações: Evidências empíricas para Chile, Brasil e México, em uma perspectiva Não Linear," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807170923500, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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