Learning over the business cycle: Policy implications

• 成果类型: Article
• 署名作者: Angeletos, George-Marios; Iovino, Luigi; La'O, Jennifer
• 署名单位: Massachusetts Institute of Technology (MIT); National Bureau of Economic Research; Bocconi University; Bocconi University; Centre for Economic Policy Research - UK; Columbia University; Federal Reserve System - USA; Federal Reserve Bank - Minneapolis
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2020.105115
• 发表日期: 2020
• 关键词: Informational frictions; learning; business cycles

摘要

This paper studies the policy implications of the endogeneity of information about the state of the economy. The business cycle can be made less noisy, and more efficient, by incentivizing firms to vary their pricing and production decisions more with their beliefs about the state of the economy. This calls for countercyclical taxes complemented by a monetary policy that leans against the wind. The optimal policies trade-off allocative efficiency for informational efficiency. (C) 2020 Elsevier Inc. All rights reserved.