Learning from Unknown Information Sources
实验发现，当信息源的准确性不确定时，人们会减少对信息的反应，尤其是好消息；分析师预测数据也验证了这一点，表明人们对信息准确性不敏感且厌恶不确定性。
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. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Y. Liang gratefully acknowledges the support of the Russell Sage Foundation (Small Grant in Behavioral Economics). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.03551 .