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)
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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.
Length: 42 pages Date of creation: May 2004 Date of revision: Handle: RePEc:iae:iaewps:wp2004n09
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2004.
"Normalization in econometrics,"
Working Paper
2004-13, Federal Reserve Bank of Atlanta.
[Downloadable!]
Other versions:
James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007.
"Normalization in Econometrics,"
Econometric Reviews,
Taylor and Francis Journals, vol. 26(2-4), pages 221-252.
[Downloadable!] (restricted)