Learning from a black box
成果类型：
Article
署名作者：
Ke, Shaowei; Wu, Brian; Zhao, Chen
署名单位：
China Europe International Business School; University of Michigan System; University of Michigan; University of Hong Kong
刊物名称：
JOURNAL OF ECONOMIC THEORY
ISSN/ISSBN：
0022-0531
DOI：
10.1016/j.jet.2024.105886
发表日期：
2024
关键词：
摘要：
We introduce a learning model in which the decision maker does not know how recommendations are generated, called the contraction rule. We present behavioral postulates that characterize it. The contraction rule can be uniquely identified and reveals how the decision maker interprets and how much she trusts the recommendation. In a dynamic stationary setting, we show that the contraction rule is not dominated by completely following recommendations and is incompatible with a property called compliance with balanced recommendations. Following this negative result, we demonstrate that the contraction rule may generate and reinforce recency bias and disagreement.