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Convergence in European GDP Series

Author

Listed:
  • Rob Luginbuhl
  • Siem Jan Koopman

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

Abstract

This discussion paper led to a publication in the Journal of Applied Econometrics . Vol. 19, issue 5, pages 611-636. Convergence in gross domestic product series of five European countriesis empirically identified using multivariate time series models that arebased on unobserved components with dynamic converging properties.We define convergence in terms of a decrease in dispersion over timeand model this decrease via mechanisms that allow for gradualreductions in the ranks of covariance matrices associated with thedisturbance vectors driving the unobserved components of the model.The inclusion of such convergence mechanisms within the formulation ofunobserved components makes the identification of various types ofconvergence possible.The common converging component model isestimated for the per capita gross domestic product of five Europeancountries: Germany, France, Italy, Spain and the Netherlands. It is foundthat convergence features in trends and cycles are present and areassociated with some key events in the history of European integration.

Suggested Citation

  • Rob Luginbuhl & Siem Jan Koopman, 2003. "Convergence in European GDP Series," Tinbergen Institute Discussion Papers 03-031/4, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20030031
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Brian M. Doyle & Jon Faust, 2005. "Breaks in the Variability and Comovement of G-7 Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 721-740, November.
    2. James H. Stock & Mark W. Watson, 2005. "Understanding Changes In International Business Cycle Dynamics," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 968-1006, September.
    3. Willie Lahari, 2011. "Assessing Business Cycle Synchronisation - Prospects for a Pacific Islands Currency Union," Working Papers 1110, University of Otago, Department of Economics, revised Oct 2011.
    4. Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
    5. Leon, Costas, 2006. "The European and the Greek Business Cycles: Are they synchronized?," MPRA Paper 1312, University Library of Munich, Germany.
    6. Andrew Hallett & Christian Richter, 2006. "Measuring the Degree of Convergence among European Business Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 229-259, May.
    7. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed? Evidence and Explanations," Working Papers 2003-2, Princeton University. Economics Department..
    8. 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.
    9. Jansen, W. Jos & Stokman, Ad C.J., 2004. "Foreign direct investment and international business cycle comovement," Working Paper Series 401, European Central Bank.
    10. 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.
    11. Ossama Mikhail, 2004. "No More Rocking Horses: Trading Business-Cycle Depth for Duration Using an Economy-Specific Characteristic," Macroeconomics 0402026, University Library of Munich, Germany.
    12. Maurizio Bovi, 2003. "Nonparametric Analysis Of The International Business Cycles," ISAE Working Papers 37, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    13. Christian Richter & Andrew Hughes Hallett, 2005. "A Time-Frequency Analysis of the Coherences of the US Business," Computing in Economics and Finance 2005 45, Society for Computational Economics.

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    Keywords

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    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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