嘉    宾：匡逸舟  助理教授 曼彻斯特大学

主持人：薛沁舒  助理教授 上海交通大学安泰经济与管理学院

时    间：2024年4月24日(周三)14:00-15:30

地    点:  上海交通大学徐汇校区安泰经济与管理学院B207

内容简介：

We propose a method to empirically decompose a cross-section of observed belief revisions into components driven by individual and common information under weak assumptions. We define a common signal as the single signal that if observed by all agents can explain the maximum amount of belief revisions across agents. Individual signals are defined to explain the residual belief revisions unaccounted for by the common signal. When applied to probability forecasts from the Survey of Professional Forecasters we find that individual signals account for more of the observed belief revisions than common signals. There is a large cross-sectional heterogeneity in signal informativeness, and the fraction of forecasters that observe individual signals that are more informative than the common signal ranges from 0.5 - 0.9, depending on variable and measure of informativeness. Unconditionally, the informativeness of individual and common signals are positively correlated. Inflation volatility, perceived stock market volatility and a high risk of recession are all factors associated with increased informativeness of both individual and common signals. We discuss the implications of our findings for theoretical models of information acquisition and we show how our procedure maps into alternative information structures.

演讲人简介：

Kyle's research primarily focuses on the intersection of econometrics and macroeconomics, covering both theoretical and applied dimensions.