IDEAS home Printed from
   My bibliography  Save this paper

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


  • van Dijk, Dick

    () (Econometric Institute, Erasmus University Rotterdam)

  • Strikholm, Birgit

    () (Dept. of Economic Statistics, Stockholm School of Economics)

  • Teräsvirta, Timo

    () (Dept. of Economic Statistics, Stockholm School of Economics)


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. 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.

Suggested Citation

  • van Dijk, Dick & Strikholm, Birgit & Teräsvirta, Timo, 2001. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," SSE/EFI Working Paper Series in Economics and Finance 0429, Stockholm School of Economics, revised 01 Jun 2004.
  • Handle: RePEc:hhs:hastef:0429 Note: Journal's pdf appears here by permission of the Royal Economic Society. Link to Econometrics Journal website:

    Download full text from publisher

    File URL:
    File Function: Appendix
    Download Restriction: no

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. David A. Pierce, 1978. "Seasonal Adjustment When Both Deterministic and Stochastic Seasonality Are Present," NBER Chapters,in: Seasonal Analysis of Economic Time Series, pages 242-280 National Bureau of Economic Research, Inc.
    2. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549.
    3. Cecchetti, Stephen G & Kashyap, Anil K & Wilcox, David W, 1997. "Interactions between the Seasonal and Business Cycles in Production and Inventories," American Economic Review, American Economic Association, vol. 87(5), pages 884-892, December.
    4. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    5. Jeffrey A. Miron, 1996. "The Economics of Seasonal Cycles," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262133237, January.
    6. Canova, Fabio & Hansen, Bruce E, 1995. "Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 237-252, July.
    7. Philip Hans Franses & Timothy J. Vogelsang, 1998. "On Seasonal Cycles, Unit Roots, And Mean Shifts," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 231-240, May.
    8. Miron, Jeffrey A & Beaulieu, J Joseph, 1996. "What Have Macroeconomists Learned about Business Cycles form the Study of Seasonal Cycles?," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 54-66, February.
    9. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    10. Lundbergh, Stefan & Terasvirta, Timo & van Dijk, Dick, 2003. "Time-Varying Smooth Transition Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 104-121, January.
    11. Canova, Fabio & Ghysels, Eric, 1994. "Changes in seasonal patterns : Are they cyclical?," Journal of Economic Dynamics and Control, Elsevier, vol. 18(6), pages 1143-1171, November.
    12. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    13. Krane, Spencer & Wascher, William, 1999. "The cyclical sensitivity of seasonality in U.S. employment," Journal of Monetary Economics, Elsevier, vol. 44(3), pages 523-553, December.
    14. Ng, S. & Perron, P., 1994. "Unit Root Tests ARMA Models with Data Dependent Methods for the Selection of the Truncation Lag," Cahiers de recherche 9423, Universite de Montreal, Departement de sciences economiques.
    15. J. Joseph Beaulieu & Jeffrey K. MacKie-Mason & Jeffrey A. Miron, 1992. "Why Do Countries and Industries with Large Seasonal Cycles Also Have Large Business Cycles?," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 621-656.
    16. Carpenter, Robert E & Levy, Daniel, 1998. "Seasonal Cycles, Business Cycles, and the Comovement of Inventory Investment and Output," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(3), pages 331-346, August.
    17. David A. Pierce, 1978. "Seasonal adjustment when both deterministic and stochastic seasonality are present," Special Studies Papers 107, Board of Governors of the Federal Reserve System (U.S.).
    18. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    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.
    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?," CESifo Working Paper Series 2272, CESifo Group Munich.
    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, March.
    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. 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.
    9. 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.
    10. 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.
    11. 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, De Gruyter Open, vol. 33(1), pages 155-186, March.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    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 Pósgraduação 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 Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].

    More about this item


    Nonlinear time series; seasonality; smooth transition autoregression; structural change; time-varying parameter;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:hastef:0429. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Helena Lundin). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.