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Global vs. group-specific business cycles: The importance of defining the groups

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  • Berger, Tino
  • Wortmann, Marcus

Abstract

The literature on international business cycles has employed dynamic factor models to disentangle global from group-specific and national factors in countries' macroeconomic aggregates. Therefore, the countries have simply been classified ex ante as belonging to the same region or the same level of development. This paper estimates a DFM for a sample of 106 countries and three variables (output, consumption, investment) over the period 1960 to 2014, in which the countries are classified according to the outcome of a cluster analysis. By comparing the results with those obtained by the previous grouping approaches, we show substantial deviations in the importance of global and group-specific factors. Remarkably, when the groups are defined properly, the 'global business cycle' accounts for only a very small fraction of macroeconomic fluctuations, most evidently in the industrialized world. The group-specific factors, on the other hand, play a much greater role for national business cycles than previously thought - also in the pre-globalization period.

Suggested Citation

  • Berger, Tino & Wortmann, Marcus, 2018. "Global vs. group-specific business cycles: The importance of defining the groups," University of Göttingen Working Papers in Economics 334, University of Goettingen, Department of Economics.
  • Handle: RePEc:zbw:cegedp:334
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    References listed on IDEAS

    as
    1. Hideaki Hirata & M. Ayhan Kose & Chris Otrok, "undated". "Regionalization vs. Globalization," Working Paper 164456, Harvard University OpenScholar.
    2. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    3. Haroon Mumtaz & Saverio Simonelli & Paolo Surico, 2011. "International Comovements, Business Cycle and Inflation: a Historical Perspective," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 176-198, January.
    4. Neville Francis & Michael T. Owyang & Ozge Savascin, 2017. "An endogenously clustered factor approach to international business cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1261-1276, November.
    5. M. Ayhan Kose & Christopher Otrok & Eswar Prasad, 2012. "Global Business Cycles: Convergence Or Decoupling?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 511-538, May.
    6. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    7. Ductor, Lorenzo & Leiva-Leon, Danilo, 2016. "Dynamics of global business cycle interdependence," Journal of International Economics, Elsevier, vol. 102(C), pages 110-127.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    international business cycles; globalization; regionalization; dynamic factormodels; cluster analysis;
    All these keywords.

    JEL classification:

    • 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
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles

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