Career: Reputation with Limited Information, Theory and Applications
Career: Reputation with Limited Information, Theory and Applications
批准号:
2337566
负责人:
Di Pei
金额:
$46.24万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-03-15 至 2029-02-28
中文摘要
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英文摘要
This award funds research in economic theory. The principal investigator plans to use game theory to understand the circumstances under which economic agents (such as firms and politicians) have incentives to take socially desirable actions in long-term relationships. The research seeks to answer the following specific questions. First, does a firm have incentives to supply a high quality product when the market has limited information about its past behavior? Second, what kind of information should online platforms provide to consumers in order to motivate sellers to build a reputation for supplying high quality product? Third, can researchers deliver robust predictions on firms’ behaviors that can be tested using data?The principal investigator will answer these questions by using novel methods in the theory of repeated games, reputation, and learning. The first project analyzes how consumers’ ability to observe other consumers’ choices (i.e., observational learning) affects each seller’s incentives to build a reputation for supplying high quality. Consumers’ information is summarized by a stochastic network, which determines whether a consumer’s action can be observed by each of their successors. The results identify network structures under which observational learning strengthens reputational incentives as well as those that cause reputational incentives to break down. The second project analyzes situations where consumers do not have detailed information about the firm’s history. The analysis sheds light on the effects of long social memories, the coarsening of market information, the heterogeneous quality of consumer information on the seller’s incentives to sustain a reputation, and on consumers’ welfare. The third project analyzes situations where long-lived agents (e.g., sellers, politicians) can manipulate their past records, for example, they can erase signals from their records at some cost. This is motivated by applications to online platforms in which sellers can bribe consumers in exchange for taking down the negative reviews. The main result shows that, when sellers are sufficiently long-lived, their returns from building reputations are entirely wiped out, even when the market suspects that they may erase records with a low probability. It also shows that players’ incentives to sustain cooperation do not necessarily increase with their expected lifespans; and this finding stands in contrast to the standard predictions found in the literature on repeated games.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Monotone Methods in Reputations: Behavioral Predictions and Reputation Sustainability
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批准号:1947021
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项目类别:Standard Grant
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资助金额:$27.7万
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财政年份:2020
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负责人:Di Pei
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依托单位:
海外基金