Learning, Monetary Policy Rules, and Macroeconomic Stability

42 Pages Posted: 16 Aug 2005

See all articles by Fabio Milani

Fabio Milani

University of California, Irvine - Department of Economics

Date Written: April 2005


This paper estimates a DSGE model with learning to reexamine the evidence on time variation in post-war U.S. monetary policy. Several papers document a regime switch, by showing that policy changed from 'passive' and destabilizing in the pre-1979 period to 'active' and stabilizing in the following decades. These papers typically work with DSGE models with rational expectations.

This paper relaxes the assumption of rational expectations and it allows for learning instead. Economic agents form expectations from simple models and update the parameters through constant-gain learning.

I estimate the model by Bayesian methods. The constant gain coefficient is jointly estimated with the structural and policy parameters of the system.

I find that the feedback coefficient to inflation was well above 1 also in the 1960s and 1970s and therefore policy was not leading to macroeconomic instability. The results reconcile the evidence from DSGE models with what obtained by time-varying VAR studies, which typically find only modest changes in policy coefficients over the post-war sample.

Keywords: monetary policy, new Keynesian DSGE model, constant-gain learning, expectations, Bayesian estimation, macroeconomic instability

JEL Classification: C11, D84, E30, E50, E52, E58

Suggested Citation

Milani, Fabio, Learning, Monetary Policy Rules, and Macroeconomic Stability (April 2005). Available at SSRN: https://ssrn.com/abstract=779207 or http://dx.doi.org/10.2139/ssrn.779207

Fabio Milani (Contact Author)

University of California, Irvine - Department of Economics ( email )

3151 Social Science Plaza
Irvine, CA 92697-5100
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics