Business Cycle Monitoring with Structural Changes

27 Pages Posted: 27 Aug 2008 Last revised: 21 Dec 2009

See all articles by Marcelle Chauvet

Marcelle Chauvet

University of California Riverside

Simon Potter

Federal Reserve Bank of New York

Date Written: August 24, 2008

Abstract

This paper examines the predictive content of coincident variables for monitoring U.S. recessions in the presence of instabilities. We propose several specifications of a probit model for classifying phases of the business cycle. We find strong evidence in favor of the ones that allow for the possibility that the economy has experienced recurrent breaks. The recession probabilities of these models provide a clearer classification of the business cycle into expansion and recession periods, and superior performance in the ability to correctly call recessions and to avoid false recession signals. Overall, the sensitivity, specificity, and accuracy of these models are far superior as well as their ability to timely signal recessions. The results indicate the importance of considering recurrent breaks for monitoring business cycles.

Keywords: Recession, Instability, Bayesian Methods, Probit model, Breaks

Suggested Citation

Chauvet, Marcelle and Potter, Simon, Business Cycle Monitoring with Structural Changes (August 24, 2008). Available at SSRN: https://ssrn.com/abstract=1251002 or http://dx.doi.org/10.2139/ssrn.1251002

Marcelle Chauvet (Contact Author)

University of California Riverside ( email )

900 University Avenue
4136 Sproul Hall
Riverside, CA 92521
United States
(951) 827-1587 (Phone)

HOME PAGE: http://https://sites.google.com/site/marcellechauvet/

Simon Potter

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States
212-720-6309 (Phone)
212-720-1844 (Fax)

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