A Markov switching factor-augmented VAR model for analyzing US business cycles and monetary policy

This paper develops a Markov switching factor-augmented vector autoregression to investigate the transmission mechanisms of monetary policy for distinct stages of the US business cycle. We assume that autoregressive parameters and covariance matrices of the error terms are regime dependent, driven by an unobserved Markov indicator. Endogenously determined transition probabilities are governed by an underlying probit model that features a large set of possible predictors. The empirical findings provide evidence for differences in the transmission of monetary policy shocks that mainly stem from heterogeneity in the responses of financial market quantities.