Monetary policy, parameter uncertainty and optimal learning

• 成果类型: Article
• 署名作者: Wieland, V
• 署名单位: Federal Reserve System - USA
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/S0304-3932(00)00023-4
• 发表日期: 2000
• 页码: 199-228
• 关键词: optimal control with unknown parameters; Bayesian learning; monetary policy; structural change; learning by doing; inflation targeting

摘要

Since central banks have limited information concerning the transmission channel of monetary policy, they are faced with the difficult task of simultaneously controlling the policy target and estimating the impact of policy actions. A tradeoff between estimation and control arises because policy actions influence estimation and provide information which may improve future performance. I analyze this tradeoff in a simple model with parameter uncertainty and conduct dynamic simulations of the policymaker's decision problem in the presence of the type of uncertainties that arose in the wake of German reunification. A policy that separates learning from control may induce a persistent upward bias in money growth and inflation, just as observed after unification. In contrast, the optimal learning strategy which exploits the tradeoff between control and estimation significantly improves stabilization performance and reduces the likelihood of inflationary bias. (C) 2000 Elsevier Science B.V. All rights reserved. JEL classification: E52; E40; D83; C44.