Measuring the impact of unconventional monetary policy on the US business cycle

The paper estimates a dynamic macroeconometric model for the US economy that captures two important features commonly observed in the study of the US business cycle, namely the strong co-movement of key macroeconomic quantities, and the distinction between expansionary and recessionary phases. The model extends the factor-augmented vector autoregressive model of Bernanke et al. (2005)
by combining Markov switching with factor augmentation, modeling the Markov switching probabilities endogenously, and adopting a full Bayesian estimation approach
which uses shrinkage priors for several parts of the parameter space. Exploiting a large data set for the US economy ranging from 1971:Q1 to 2014:Q2, the model is applied to measure not only the dynamic effects of unconventional monetary policy within distinct stages of the business cycle, but also the dynamic
response of the recession probabilities, based on conducting counterfactual simulations.
The results obtained provide new insights on the effect of monetary policy under changing business cycle phases, and highlight the importance of discriminating
between expansionary and recessionary phases of the business cycle when analyzing the impact of monetary policy on the macroeconomy.