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How Well Do Markov Switching Models Describe Actual Business Cycles? The Case of Synchronization

  • Penelope A. Smith

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

  • Peter M. Summers

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

The objective of this paper is to evaluate the effectiveness of using a Markov switching model to measure the synchronization of business cycles. We use a Bayesian, Gibbs sampling approach to estimate a multivariate Markov switching model of GDP growth for several countries. We look for evidence of synchronization across countries in the sense of common Markov states, covariance of impulses and a long-run co-integrating relationship. We then use the fitted data implied by the posterior distribution of the Markov switching VAR, in conjunction with a dating rule, to obtain the posterior distribution of binary business cycle states. We use these to investigate the posterior distributions of non-parametric measures of synchronization described by Harding and Pagan (2003) and compare them with similar measures obtained from standard reference chronologies. As a point of reference, we repeat this exercise using simulated data from a linear VAR. We find no evidence of a common Markov state, but some evidence of the propagation of country-specific disturbances across countries and of a co-integrating relationship between the United States and Canada. Posterior odds ratios overwhelmingly favor the Markov switching model over the linear VAR and we find that the posterior distributions of the non-parametric measures of synchronisation produced by the Markov switching VAR match the data more closely than those produced by the linear VAR.

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Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2004n09.

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Length: 42 pages
Date of creation: May 2004
Date of revision:
Handle: RePEc:iae:iaewps:wp2004n09
Contact details of provider: Postal: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia
Phone: +61 3 8344 2100
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Web page: http://www.melbourneinstitute.com/
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  3. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
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  8. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, June.
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  16. 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, May.
  17. Penelope A. Smith & Peter M. Summers, 2002. "Regime Switches in GDP Growth and Volatility: Some International Evidence and Implications for Modelling Business Cycles," Melbourne Institute Working Paper Series wp2002n21, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  18. J. Michael Durland & Thomas H. McCurdy, 1993. "Duration Dependent Transitions in a Markov Model of U.S. GNP Growth," Working Papers 887, Queen's University, Department of Economics.
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  20. 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.
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