講座：Learning from Unknown Information Sources
題 目：Learning from Unknown Information Sources
演講人：Yucheng Liang (梁禹澄), Research Affiliate, Briq Institute
主持人：李淑雯 助理教授 上海交通大學安泰經濟與管理學院
時 間：2020年 10月28日（周三） 14:30 - 16:00
When an agent receives information generated by a source whose accuracy might either be high or low, standard economic theory dictates that she update as if the source has medium accuracy. In a lab experiment, I find that subjects' updating behaviors deviate from this benchmark. First, subjects under-react to information when the source is uncertain. Second, the under-reaction is more pronounced for good news than for bad news. These two patterns, under-reaction and pessimism, are consistent with a theory of belief updating where agents are insensitive and averse to compound uncertainty and ambiguity. I also find that subjects' reactions to information with uncertain accuracy are uncorrelated with their evaluations of bets with uncertain odds. This suggests that people have distinct attitudes toward uncertainty in information accuracy and uncertainty in economic fundamentals. The experimental results are validated using observational data on stock price reactions to analyst earnings forecasts, where analysts with no forecast records are classified as uncertain information sources.
Dr. Yucheng Liang is a research affiliate at the briq Institute at Bonn, Germany. Dr. Liang uses theoretical and empirical methods to study behavioral economics. His current research focuses on uncertainty, information, and communication with applications in finance and management. Dr. Liang received a Ph.D. in Economics from Stanford Graduate School of Business and will join the faculty of Carnegie Mellon University next year.