摘要翻译:
基于数据的决策必须考虑到代理对数据的操作,这些代理知道决策是如何做出的,并希望影响它们的分配。我们研究了一个框架,在这个框架中,由于这样的操作,当决策更强烈地依赖于数据时,数据变得不那么信息量。我们正式确定了决策者为什么以及如何承诺对数据的利用不足。这样做可以减少信息损失,从而提高分配精度。
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英文标题:
《Improving Information from Manipulable Data》
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作者:
Alex Frankel and Navin Kartik
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最新提交年份:
2021
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分类信息:
一级分类:Economics 经济学
二级分类:Theoretical Economics 理论经济学
分类描述:Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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英文摘要:
Data-based decisionmaking 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 becomes less informative when decisions depend more strongly on data. We formalize why and how a decisionmaker should commit to underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy.
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PDF链接:
https://arxiv.org/pdf/1908.10330