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Measuring Synchronisation and Convergence of Business Cycles

Author

Listed:
  • Siem Jan Koopman

    () (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

  • Joao Valle e Azevedo

    () (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

Abstract

This discussion paper resulted in an article in the Oxford Bulletin of Economics and Statistics (2008). Vol. 70 issue 1, pages 23-51. This paper investigates business cycle relations among different economies in theEuro area. Cyclical dynamics are explicitly modelled as part of a time series model. Weintroduce mechanisms that allow for increasing or diminishing phase shifts and for time-varyingassociation patterns in different cycles. Standard Kalman filter techniques are used toestimate the parameters simultaneously by maximum likelihood. The empirical illustrationsare based on gross domestic product (GDP) series of seven European countries which are comparedwith the GDP series of the Euro Area and that of the United States. The original integratedtime series are band-pass filtered. We find that there is an increasing resemblance between thebusiness cycle fluctuations of the European countries analysed and those of the Euro area,although with varying patterns.

Suggested Citation

  • Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20030052
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    File URL: http://papers.tinbergen.nl/03052.pdf
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    References listed on IDEAS

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    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. Don Harding & Adrian Pagan, 1999. "Dissecting the Cycle," Melbourne Institute Working Paper Series wp1999n13, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    3. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    4. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    5. 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.
    6. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    7. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    8. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    9. Artis, Michael J & Zhang, W, 1997. "International Business Cycles and the ERM: Is There a European Business Cycle?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(1), pages 1-16, January.
    10. 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.
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    Citations

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    Cited by:

    1. Matthieu Lemoine, 2006. "Annex A5 : A model of the stochastic convergence between euro area business cycles," Working Papers hal-00972793, HAL.
    2. Bertrand Candelon & Jan Piplack & Stefan Straetmans, 2009. "Multivariate Business Cycle Synchronization in Small Samples," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 715-737, October.
    3. Ageliki Anagnostou & Ioannis Panteladis & Maria Tsiapa, 2015. "Disentangling different patterns of business cycle synchronicity in the EU regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 615-641, August.
    4. Philippe Moës, 2006. "The production function approach to the Belgian output gap, estimation of a multivariate structural time series model," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(1), pages 59-91.
    5. Marco Percoco, 2016. "Labour Market Institutions: Sensitivity to the Cycle and Impact of the Crisis in European Regions," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(3), pages 375-385, July.
    6. Jakob de Haan & Robert Inklaar & Richard Jong-A-Pin, 2008. "Will Business Cycles In The Euro Area Converge? A Critical Survey Of Empirical Research," Journal of Economic Surveys, Wiley Blackwell, vol. 22(2), pages 234-273, April.
    7. Matteo M. Pelagatti, 2005. "Business cycle and sector cycles," Econometrics 0503006, University Library of Munich, Germany.
    8. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil III: Konvergenz," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(15), pages 23-32, August.
    9. Hasan Engin Duran, 2015. "Dynamics of Business Cycle Synchronization in Turkey," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 62(5), pages 581-606, December.
    10. Hasan Engin Duran, 2015. "Dynamics of Business Cycle Synchronization within Turkey," Working Papers 2015/01, Turkish Economic Association.
    11. Matthieu Lemoine, 2005. "A model of the stochastic convergence between business cycles," Documents de Travail de l'OFCE 2005-05, Observatoire Francais des Conjonctures Economiques (OFCE).
    12. Siklos, Pierre L., 2012. "No coupling, no decoupling, only mutual inter-dependence : Business cycles in emerging vs. mature economies," BOFIT Discussion Papers 17/2012, Bank of Finland, Institute for Economies in Transition.

    More about this item

    Keywords

    Band-pass filter; Cyclical convergence; Kalman filter; Unobserved components time series models; Phase shifts.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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