2024/01/18 by Huber, Florian, Fischer, Manfred M.
paper · doi:10.57938/c87ebc08-10b3-4321-955b-420153467ae0
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) <br/>by combining Markov switching with factor augmentation, modeling the Markov switching probabilities endogenously, and adopting a full Bayesian estimation approach <br/>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 <br/>response of the recession probabilities, based on conducting counterfactual simulations. <br/>The results obtained provide new insights on the effect of monetary policy under changing business cycle phases, and highlight the importance of discriminating <br/>between expansionary and recessionary phases of the business cycle when analyzing the impact of monetary policy on the macroeconomy.