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Classical and modern business cycle measurement: The European case

  • Hans-Martin Krolzig

    ()

  • Juan Toro

    ()

This paper intends to harmonize two different approaches employed in the analysis of business cycles 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. The stylized facts retrieved are commented and compared to those obtained by Harding and Pagan (2002) for the U.S.. Two conclusions can be extracted from the results: a) though the turning points obtained for individual countries seem to cluster and would suggest the idea of a common cycle, there are relevant differences in the stylized facts characterizing the business cycle in the individual European economies under analysis; b) moreover, we find relevant differences in the business cycle stylized facts of the European countries and the U.S., mostly in terms of the duration, the amplitude of the cycle and the shape of the recovery. We then adopt the ‘modern’ alternative: the Markov-switching vector autoregression (MS-VAR). 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. Contrary to the results reported by Harding and Pagan (2002) , we show that the MS-VAR model is a good candidate to be used as an statistical instrument to improve the understanding of the business cycle. Copyright Springer-Verlag Berlin/Heidelberg 2004

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Article provided by Springer in its journal Spanish Economic Review.

Volume (Year): 7 (2004)
Issue (Month): 1 (January)
Pages: 1-21

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Handle: RePEc:spr:specre:v:7:y:2004:i:1:p:1-21
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  1. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
  2. Wesley Clair Mitchell, 1951. "What Happens During Business Cycles: A Progress Report," NBER Books, National Bureau of Economic Research, Inc, number mitc51-1.
  3. Krozlig, H.M., 1997. "International Business Cycles: Regime Shifts in the Stochastic Process of Economic Growth," Economics Series Working Papers 99194, University of Oxford, Department of Economics.
  4. 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 269-77, July.
  5. Gregory D. Hess & Shigeru Iwata, 1995. "Measuring business cycle features," Research Working Paper 95-10, Federal Reserve Bank of Kansas City.
  6. Artis, Michael J & Zhang, Wenda, 1995. "International Business Cycles and the ERM: Is there a European Business Cycle?," CEPR Discussion Papers 1191, C.E.P.R. Discussion Papers.
  7. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
  8. Bruce E. Hansen, 1995. "Erratum: The Likelihood ratio Test Under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Boston College Working Papers in Economics 296., Boston College Department of Economics.
  9. 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.
  10. 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 357-84, March.
  11. Hess, Gregory D & Iwata, Shigeru, 1997. "Measuring and Comparing Business-Cycle Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 432-44, October.
  12. Robin L. Lumsdaine & Eswar S. Prasad, 1997. "Identifying the Common Component in International Economic Fluctuations," NBER Working Papers 5984, National Bureau of Economic Research, Inc.
  13. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De.
  14. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
  15. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
  16. Adrian Pagan, 1997. "Towards an Understanding of Some Business Cycle Characteristics," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 30(1), pages 1-15.
  17. Phillips, Kerk L., 1991. "A two-country model of stochastic output with changes in regime," Journal of International Economics, Elsevier, vol. 31(1-2), pages 121-142, August.
  18. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-36, April.
  19. Pagan, Adrian, 1997. "Policy, Theory, and the Cycle," Oxford Review of Economic Policy, Oxford University Press, vol. 13(3), pages 19-33, Autumn.
  20. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
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