Juan Francisco Rubio-Ramírez, Daniel Waggoner, and Tao Zha
Working Paper 2005-27
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.
JEL classification: C32, E10
Key words: Markov switching, regime changes, volatility, identification
The authors thank Fabio Canova, Jon Faust, Ellis Tallman, Harald Uhlig, and especially Jim Nason for helpful discussions and comments. Eric Wang provided excellent research assistance. The authors greatly acknowledge the technical support of parallel computing from the Computing College of the Georgia Institute of Technology. The views expressed here are the authors’ and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors’ responsibility.
Please address questions regarding content to Juan Francisco Rubio-Ramírez, Federal Reserve Bank of Atlanta, 1000 Peachtree Street, N.E., Atlanta, GA 30309, 404-498-8057, firstname.lastname@example.org; Daniel Waggoner, Federal Reserve Bank of Atlanta, 1000 Peachtree Street, N.E., Atlanta, GA 30309, 404-498-8278; or Tao Zha, Federal Reserve Bank of Atlanta, 1000 Peachtree Street, N.E., Atlanta, GA 30309, 404-498-8353, email@example.com.