Imperfect Knowledge, Adaptive Learning, and the Bias Against Activist Monetary Policies

by Alberto Locarno
Research Department, Banca d’Italia and London School of Economics

Abstract

The paper studies the implications for the effectiveness of discretionary monetary policymaking of departing from the assumption of rational expectations. Society, whose welfare function is quadratic, can appoint a central banker whose preferences are either quadratic or lexicographic, to achieve the best mix of inflation and output stability. The focus on lexicographic preferences is justified on the grounds that they imply a strict ordering of policy objectives, which is typical of the mandate of several central banks. Both the private sector and the monetary policymaker have incomplete knowledge of the working of the economy and rely upon adaptive learning to form expectations and decide policy moves. The model economy is assumed to be subject to recurrent unobserved shifts, and the monetary authority, who has private information on the shocks hitting the economy, cannot credibly commit. The main finding of the paper is that when agents rely on an adaptive learning technology, a bias against activist policies arises. The paper also shows that when society has quadratic utility, a strategy based on a strict ordering of objectives is close to optimal for a wide range of values of the inflation aversion parameter.

JEL Codes: E52, E31, D84.

 
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