Learning About Monetary Policy Rules When Long-Horizon Expectations Matter

Abstract

This paper considers the implications of an important source of model misspecification for the design of monetary policy rules: the assumed manner of expectations formation. Following a considerable literature on learning, it is assumed that private agents seek to maximize their objectives subject to standard constraints and the restriction of using an econometric model to make inferences about future uncertainty. Agents do not know other agents’ tastes or beliefs and therefore do not have a complete economic model with which to derive true probability laws. Because agents solve a multi-period decision problem, their actions depend on forecasts of macroeconomic conditions many periods into the future, unlike the analysis of the Bullard and Mitra (2002) and Evans and Honkapohja (2002). The central question addressed is whether the learning dynamics converge to the equilibrium predicted by rational expectations equilibrium analysis. This question is considered for several prominent instrument rules for the determination of the nominal interest rate. A key result is that a Taylor rule ensures convergence to rational expectations equilibrium, if the so-called Taylor principle is satisfied, under any of a broad class of specifications of the learning dynamics. This suggests the Taylor rule to be desirable from the point of view of eliminating instability due to self-fulfilling expectations. A companion paper, Preston (2002b), demonstrates that several policy rules argued to be desirable in the recent literature on monetary policy and learning frequently lead to the propagation of self-fulfilling expectations and hence economic instability.