Collaborative Research: Evidence in Economic Models

合作研究：经济模型的证据

• 批准号: 1919319
• 负责人: Barton Lipman
• 金额: $ 22.9万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1919319&HistoricalAwards=false
• 关键词: Collaborative; Research; Evidence; Economic; Models

This award funds research in economic theory. The team will study the acquisition and use of hard information or evidence which enables interested parties to prove some assertions they wish to make. When can social institutions be designed in such a way as to provide strong enough incentives to interested parties to acquire enough sufficiently credible evidence as to enable efficient outcomes? When efficiency is not possible, what is the nature of the distortions from efficiency generated by the best institutions that are possible? The research team will develop mathematical models for studying these questions, including tools for making the analysis sufficiently tractable to yield clear results. More broadly, the work will facilitate research of applied economic models in this large class of interesting environments. By providing tools for making the analysis more tractable, the research may generate new classes of economic institutions and shed new light on existing ones. The tools will also be useful in studying the structure of organizations, such as firms and governments. The project focuses on mechanism design when agents can acquire noisy evidence. The general model has connections to a wide range of economic models of "hard information", such as Bayesian persuasion and models of testing. The team will develop tools for simplifying the mechanism design problem to be able to focus on a more tractable class of mechanisms. In particular, they will develop conditions under which one can identify the evidence the principal will request given any claim by the agent and/or the evidence generation actions the principal will recommend given any type report. Together or separately, this identification will greatly simplify characterization of the optimal mechanism. The investigators will also compare optimal mechanisms to outcomes when the principal cannot commit himself. Finally, they will characterize environments in which efficient outcomes are possible and the nature of distortions when efficiency is not achievable.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.

该奖项资助经济理论研究。该小组将研究如何获取和使用确凿的信息或证据，使有关各方能够证明他们希望提出的某些主张。什么时候社会制度才能被设计成能够为利益相关方提供足够强有力的激励，以获得足够可信的证据，从而实现有效的结果？当效率不可能实现时，由可能的最佳机构产生的效率扭曲的性质是什么？该研究小组将开发用于研究这些问题的数学模型，包括使分析足够容易得到明确结果的工具。更广泛地说，这项工作将促进在这一大类有趣的环境中应用经济模型的研究。通过提供使分析更易于处理的工具，研究可能会产生新的经济制度类别，并对现有的经济制度进行新的阐述。这些工具在研究企业和政府等组织的结构方面也很有用。该项目的重点是机制设计时，代理人可以获得噪音的证据。一般模型与广泛的“硬信息”经济模型有联系，如贝叶斯说服和测试模型。该团队将开发工具，简化机制设计问题，以便能够专注于更易于处理的机制类。特别是，他们将制定条件，在这些条件下，可以确定委托人将要求代理人提出任何索赔的证据和/或委托人将建议任何类型报告的证据生成行动。共同或单独地，这种识别将大大简化最佳机制的表征。调查人员还将比较最佳机制与校长无法承诺时的结果。最后，他们将描述环境中，有效的结果是可能的和扭曲的性质时，效率是无法实现的。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。