Learning from Unknown Information Sources

• 成果类型: Article
• 署名作者: Liang, Yucheng
• 署名单位: Carnegie Mellon University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2021.03551
• 发表日期: 2025
• 关键词: Belief updating; ambiguity; compound risk; EARNINGS FORECASTS

摘要

When an agent receives information from a source whose accuracy might be either high or low, standard theory dictates that she update as if the source has medium accuracy. In a laboratory experiment, subjects deviate from this benchmark by reacting less to uncertain sources, especially when the sources release good news. This pattern is validated using observational data on stock price reactions to analyst earnings forecasts, where analysts with no forecast records are classified as uncertain sources. A theory of belief updating where agents are insensitive and averse to information accuracy uncertainty can explain these results.