Topics in Matching

该奖项资助了关于不完全信息环境下匹配的新经济理论。匹配模型使用博弈论的技术来研究两个合作伙伴必须“匹配”才能进行交易的情况。例子包括将工人与雇主匹配，将学生与学校匹配。该项目分为两部分。第一部分研究了代理人对生产性特征的投资激励。在很多情况下，配对的价值取决于双方在配对前的投资。例如，教师和学校之间匹配的价值取决于教师的教育，培训和经验。这也取决于学校的物理设备和设施。双方都必须在比赛前进行投资，但如果他们担心未来的合作伙伴会通过众所周知的“拖延问题”来利用他们的投资，他们可能就没有投资的动机。在这里，pi将考虑具体的谈判协议和产权如何导致有效的投资。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。有大量的文献使用匹配模型来分析各种各样的应用。这些应用程序中常用的解决方案概念是核心。核心作为解决方案概念的使用包含了工人和企业之间拟议匹配的稳定性；如果提议的结果不在核心范围内，我们预计结果将被能够共同改善其处境的两家公司所打乱。然而，这一论点依赖于信息完备的假设。pi开发了一个概念，定义了不完全信息环境中的成对稳定性。他们研究了各种模型对不完全信息的鲁棒性，并考虑了多对一匹配问题。本课题为大型应用文献的匹配提供了较好的基础。现有的匹配理论通过应用于市场设计而产生了实质性的更广泛的影响。这些方法用于匹配学生和学校，医学毕业生和住院医师，以及移植供体和接受者。新理论可能会提高这些机制的经济性能。

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.