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Markov-switching structural vector autoregressions: theory and application

  • Juan Francisco Rubio-Ramírez
  • Daniel Waggoner
  • Tao Zha

This paper develops a new and easily implementable necessary and sufficient condition for the exact identification of a Markov-switching structural vector autoregression (SVAR) model. The theorem applies to models with both linear and some nonlinear restrictions on the structural parameters. We also derive efficient MCMC algorithms to implement sign and long-run restrictions in Markov-switching SVARs. Using our methods, four well-known identification schemes are used to study whether monetary policy has changed in the euro area since the introduction of the European Monetary Union. We find that models restricted to only time-varying shock variances dominate the other models. We find a persistent post-1993 regime that is associated with low volatility of shocks to output, prices, and interest rates. Finally, the output effects of monetary policy shocks are small and uncertain across regimes and models. These results are robust to the four identification schemes studied in this paper.

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Paper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 2005-27.

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Date of creation: 2005
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Handle: RePEc:fip:fedawp:2005-27
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