Topics in Matching

这个奖项为关于不完全信息环境中匹配的新经济理论提供了资金。匹配模型使用博弈论中的技术来研究两个伙伴必须“匹配”才能进行交易的情况。例如为工人配对雇主和为学生配对学校。这项计划分为两部分。第一部分研究代理人对生产性特征的投资激励。在许多情况下，配对的价值取决于双方在配对前所做的投资。例如，教师与学校匹配的价值取决于教师的教育、培训和经验。这还取决于学校提供的实物设备和设施。双方都必须在比赛前投资，但如果他们担心未来的合作伙伴会通过众所周知的“阻碍问题”利用他们的投资，他们可能没有投资的动机。这里，私人投资机构将考虑具体的讨价还价协议和产权如何能够带来有效的投资。研究的第二部分考虑了不完全信息下匹配结果稳定性的含义。有大量文献使用匹配模型来分析各种应用程序。这些应用程序中常用的解决方案概念是核心。使用核心作为解决方案的概念包含了工人和公司之间拟议匹配的稳定性；如果拟议的结果不在核心中，我们预计结果将被这两个人打乱，从而共同改善他们的情况。然而，这一论点依赖于一个完全信息的假设。PI定义了在不完全信息环境下的成对稳定性。他们研究了各种模型对不完全信息的稳健性，并考虑了多对一匹配问题。这个项目为匹配方面的大量应用文献提供了更好的基础。现有的匹配理论通过应用于市场设计产生了相当广泛的影响。这些方法被用来匹配学生与学校，医学毕业生与住院医生，以及将捐赠者移植给接受者。新的理论可能会提高这些机制的经济绩效。

This award funds new economic theory on matching in environments with incomplete information. Matching models use techniques from game theory to study situations in which two partners must be 'matched' in order to make a trade. Examples include matching workers to employers and matching students to schools.The project has two parts. The first part studies agents' incentives to invest in productive characteristics. In many situations, the value of a match depends on investments the partners have made before their match. For example, the value of a match between a teacher and a school depends on the teacher's education, training and experience. It also depends on the physical equipment and facilities available at the school. Both parties must invest before the match, but they may not have incentives to invest if they fear that their future partners will take advantage of their investment through the well-known 'hold up problem'. Here, the PIs will consider how specific bargaining protocols and property rights can lead to efficient investments. The second part of the research considers the implications of stability of matching outcomes under incomplete information. There is a large literature that uses matching models to analyze a broad variety of applications. The commonly employed solution concept in these applications is the core. The use of the core as a solution concept incorporates the stability of a proposed matching between workers and firms; if the proposed outcome is not in the core we would expect the outcome to be upset by the pair that could jointly improve their circumstances. This argument, however, relies on an assumption of complete information. The PIs develop a concept that defines pairwise stability in incomplete information environments. They investigate the robustness of various models to incomplete information and consider many-to-one matching problems. This project provides better foundations for the large applied literature in matching.Existing theories of matching have had substantial broader impact through their application to market design. These methods are used to match students to schools, medical graduates to residencies, and transplant donors to recipients. The new theory may improve the economic performance of these mechanisms.