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Classical And Modern Business Cycle Measurement: The European Case

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  • Krolzig, H.-M.
  • Toro, J.

Abstract

his paper intends to harmonize two different approaches to the analysis of the business cycle and in doing so it retrieves the stylized facts of the business cycle in Europe. We start with the classical' approach proposed in Burns and Mitchell (1946) of dating and analyzing the business cycle; we then adopt the modern' alternative: the Markov-switching time series model proposed in Hamilton (1989a). The model's regime probabilities provide an optimal statistical inference of the turning point of the European business cycle. For assessing the capacity of the parametric approach to generate the stylized facts of the classical cycle in Europe, the stylized facts of the original data are compared to those of simulated data. The MS VAR model is shown to be a good candidate for use as a statistical instrument to improve the understanding of the business cycle.

Suggested Citation

  • Krolzig, H.-M. & Toro, J., 2001. "Classical And Modern Business Cycle Measurement: The European Case," Economics Series Working Papers 9960, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:9960
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    References listed on IDEAS

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    Cited by:

    1. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
    2. Camacho, Maximo & Perez-Quiros, Gabriel & Saiz, Lorena, 2008. "Do European business cycles look like one?," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2165-2190, July.
    3. Pilar Bengoechea & Gabriel Pérez Quirós, 2004. "A useful tool to identify recessions in the euro area," European Economy - Economic Papers 2008 - 2015 215, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. Marie Adanero-Donderis & Olivier Darné & Laurent Ferrara, 2009. "Un indicateur probabiliste du cycle d'accélération pour l'économie française," Economie & Prévision, La Documentation Française, vol. 0(3), pages 95-114.
    5. Brüggemann, Ralf & Riedel, Jana, 2011. "Nonlinear interest rate reaction functions for the UK," Economic Modelling, Elsevier, vol. 28(3), pages 1174-1185, May.
    6. Bessec Marie & Bouabdallah Othman, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-24, June.
    7. Sumru Altug & Bilin Neyapti & Mustafa Emin, 2012. "Institutions and Business Cycles," International Finance, Wiley Blackwell, vol. 15(3), pages 347-366, December.
    8. Emanuel Mönch & Harald Uhlig, 2003. "Towards a Monthly Business Cycle Chronology for the Euro Area," SFB 649 Discussion Papers SFB649DP2005-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany, revised Apr 2005.
    9. Aka, B.F., 2004. "Do WAEMU Countries Exhibit a Regional Business Cycle?. A Simulated Markov Switching Model for a Western Africa area," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 4(4).
    10. Laurent Ferrara & Dominique Guegan, 2006. "Real-time detection of the business cycle using SETAR models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00185372, HAL.
    11. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, September.
    12. Eric Girardin, 2004. "Regime-Dependent Synchronization of Growth Cycles between Japan and East Asia," Asian Economic Papers, MIT Press, vol. 3(3), pages 147-176.
    13. Caraiani, Petre, 2012. "Stylized facts of business cycles in a transition economy in time and frequency," Economic Modelling, Elsevier, vol. 29(6), pages 2163-2173.
    14. Carlo Altavilla, 2004. "Do EMU Members Share the Same Business Cycle?," Journal of Common Market Studies, Wiley Blackwell, vol. 42(5), pages 869-896, December.
    15. Adanero-Donderis , M. & Darné, O. & Ferrara, L., 2007. "Deux indicateurs probabilistes de retournement cyclique pour l’économie française," Working papers 187, Banque de France.
    16. Michael Artis, 2002. "Dating the Business Cycle in Britain," National Institute Economic Review, National Institute of Economic and Social Research, vol. 182(1), pages 90-95, October.
    17. Maximo Camacho & Gabriel Perez-Quiros & Lorena Saiz & Universidad de Murcia, 2006. "Do european business cycles look like one $\_?$," Computing in Economics and Finance 2006 175, Society for Computational Economics.
    18. AKA, Bédia F., 2009. "Business Cycle And Sectoral Fluctuations: A Nonlinear Model For Côte D’Ivoire," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 9(1), pages 111-126.

    More about this item

    Keywords

    BUSINESS CYCLES ; TIME SERIES ; STATISTICAL INSTRUMENTS;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • 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

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