A Factor Augmented Vector Autoregressive (FAVAR) approach for Monetary Policy: Replication of the empirical results in “Measuring the effects of Monetary Policy”

In recent paper, Bernanke, Boivin and Eliasz’s (2005) study presented a model of how the monetary policy rate affects the large subset of the variables that the researcher and policy-maker care about. Several criticisms of the Vector autoregression (VAR) approach which is developed by the considerable literature of Bernanke and Blinder (1992) and Sims (1992) to monetary policy identification center around the relatively small amount of information used by low-dimensional VARs. In that case, FAVAR methodology leads to broadly plausible estimates for the responses of a wide variety of macroeconomic variables to monetary policy shocks. Bernanke, Boivin and Eliasz also provided empirical support for this model based on an analysis of the federal fund rate and other macroeconomic indicators of US economy between the early 1959s and late 2001. This paper replicates the main empirical findings of Bernanke, Boivin and Eliasz (2005).