Learning under ambiguity
成果类型：
Article
署名作者：
Epstein, Larry G.; Schneider, Martin
署名单位：
Boston University; New York University; National Bureau of Economic Research
刊物名称：
REVIEW OF ECONOMIC STUDIES
ISSN/ISSBN：
0034-6527
DOI：
10.1111/j.1467-937X.2007.00464.x
发表日期：
2007
页码：
1275-1303
关键词：
摘要：
This paper considers learning when the distinction between risk and ambiguity matters. It first describes thought experiments, dynamic variants of those provided by Ellsberg, that highlight a sense in which the Bayesian learning model is extreme-it models agents who are implausibly ambitious about what they can learn in complicated environments. The paper then provides a generalization of the Bayesian model that accommodates the intuitive choices in the thought experiments. In particular, the model allows decision-makers' confidence about the environment to change-along with beliefs-as they learn. A portfolio choice application compares the effect of changes in confidence under ambiguity vs. changes in estimation risk under Bayesian learning. The former is shown to induce a trend towards more stock market participation and investment even when the latter does not.