Conference Paper

Empirical and policy performance of a forward-looking monetary model

Abstract: In this paper we consider the policy implications of a fully specified dynamic general equilibrium model, developed by Smets and Wouters (2003a). This is a relatively large-scale forward looking model, which was shown to provide a good fit to the data. However there has been little previous work analyzing monetary policy within such a model. We first re-examine the empirical performance of the model. We show that systematically accounting for prior uncertainty leads to substantially different parameter estimates. However many of the qualitative features of the model remain similar under the alternative estimates that we find. We then formulate and analyze optimal policy rules in the model. In addition a standard, but ad hoc, loss function we derive and justify a utility-based loss function for the model. We determine the optimal equilibrium dynamics under both loss functions and under both sets of parameter estimates. Then we discuss alternative ways of implementing the optimal equilibrium. We find that there is much scope for indeterminacy in the model, and that optimal policy rules developed for one set of estimates may perform poorly if the economy is governed by the other set. We finally turn to the analysis of simple policy rules, finding that for the simple loss function these rules perform relatively well and are robust to different parameter estimates. Overall, our results suggest that the model may be relatively robust in its ability to capture certain aspects of the data. However some caution should be exercised in using the structural estimates, and in particular it may be dangerous to pursue fully optimal policy in such complex models.

Keywords: Monetary policy; Interest rates;

Status: Published in Interest rates and monetary policy : a conference (2004: March 19-20)

Bibliographic Information

Provider: Federal Reserve Bank of San Francisco

Part of Series: Proceedings

Publication Date: 2004

Issue: Mar