Data revisions and the identification of monetary policy shocks

Abstract

Monetary policy research using time-series methods has been criticized for using more information than the Federal Reserve had available. To quantify the role of this criticism, we estimate VARs with real-time data while accounting for the latent nature of many economic variables, such as output. Our estimated monetary policy shocks are closely correlated with typically estimated measures. The impulse response functions are broadly similar across estimation methods. Our evidence suggests that the use of revised data in VAR analyses of monetary policy shocks may not be a serious limitation for recursively identified systems, but presents more challenges for simultaneous systems.