Heterogeneity, Inattention, and Bayesian Updates

• 成果类型: Article
• 署名作者: Giacomini, Raffaella; Skreta, Vasiliki; Turen, Javier
• 署名单位: University of London; University College London; University of Texas System; University of Texas Austin; Center for Economic & Policy Research (CEPR); Pontificia Universidad Catolica de Chile
• 刊物名称: AMERICAN ECONOMIC JOURNAL-MACROECONOMICS
• ISSN/ISSBN: 1945-7707
• DOI: 10.1257/mac.20180235
• 发表日期: 2020
• 页码: 282-309
• 关键词: information; forecasts; DISAGREEMENT; expectations; BIAS

摘要

We formulate a theory of expectations updating that fits the dynamics of accuracy and disagreement in a new survey of professional forecasters. We document new stylized facts, including the puzzling persistence of disagreement as uncertainty resolves. Our theory explains these facts by allowing for different channels of heterogeneity. Agents produce an initial forecast based on heterogeneous priors and are heterogeneously inattentive. Updaters use Bayes' rule and interpret public information using possibly heterogeneous models. Structural estimation of our theory supports the conclusion that in normal times heterogeneous priors and inattention are enough to generate persistent disagreement, but not during the crisis.