2007/12/01 by Marcelle Chauvet, Jeremy Piger
Economics, Econometrics and Finance · #Financial Risk and Volatility Modeling #Global Financial Crisis and Policies #Monetary Policy and Economic Impact
paper · doi:10.1198/073500107000000296
openalex publication_date 2007/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
We evaluate the ability of formal rules to establish U.S. business cycle turning point dates in real time. We consider two approaches, a nonparametric algorithm and a parametric Markov-switching dynamic-factor model. Using a new “real-time” dataset of coincident monthly variables, we find that both approaches would have accurately identified the NBER business cycle chronology had they been in use over the past 30 years, with the Markov-switching model most closely matching the NBER dates. Further, both approaches, and particularly the Markov-switching model, yielded significant improvement over the NBER in the speed with which business cycle troughs were identified.