Optimally Imprecise Memory and Biased Forecasts

• 成果类型: Article
• 署名作者: da Silveira, Rava Azeredo; Sung, Yeji; Woodford, Michael
• 署名单位: Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); Universite PSL; Ecole Normale Superieure (ENS); Sorbonne Universite; University of Basel; Federal Reserve System - USA; Federal Reserve Bank - San Francisco; Columbia University
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.20201806
• 发表日期: 2024
• 页码: 3075-3118
• 关键词: expectations; time

摘要

We propose a model of optimal decision-making subject to a memory constraint in the spirit of models of rational inattention. Our theory differs from that of Sims ( 2003 ) in not assuming costless memory of past cognitive states. The model implies that both forecasts and actions will exhibit idiosyncratic random variation; that average beliefs will exhibit a bias that fluctuates forever; and that more recent news will be given disproportionate weight in forecasts. The model provides a simple explanation for the overreaction to news observed in the laboratory by Afrouzi et al. (2023).