Improving Information from Manipulable Data
成果类型：
Article
署名作者：
Frankel, Alex; Kartik, Navin
署名单位：
University of Chicago; Columbia University
刊物名称：
JOURNAL OF THE EUROPEAN ECONOMIC ASSOCIATION
ISSN/ISSBN：
1542-4766
DOI：
10.1093/jeea/jvab017
发表日期：
2022
页码：
79-115
关键词：
摘要：
Data-based decision making must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations. We study a framework in which, due to such manipulation, data become less informative when decisions depend more strongly on data. We formalize why and how a decision maker should commit to underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy.
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