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约束条件下的公平匹配:理论与应用

Fair Matching under Constraints: Theory and Applications
Review of Economic Studies · 2023 · Yuichiro Kamada、Fuhito Kojima

中文摘要

本文研究带有约束的一般匹配模型。注意到稳定匹配通常不存在,我们关注可行的、个体理性的且公平的匹配。我们通过某一函数的不动点刻画了此类匹配。基于这一结果,我们刻画了个体学校上的约束类别,在该约束类别下存在学生最优公平匹配,即在满足上述三个合意性质的匹配中最受每个学生偏好的匹配。我们使用政府组织的日托分配数据研究了我们理论的数值相关性。

Abstract

Abstract This paper studies a general model of matching with constraints. Observing that a stable matching typically does not exist, we focus on feasible, individually rational, and fair matchings. We characterize such matchings by fixed points of a certain function. Building on this result, we characterize the class of constraints on individual schools under which there exists a student-optimal fair matching, the matching that is the most preferred by every student among those satisfying the three desirable properties. We study the numerical relevance of our theory using data on government-organized daycare allocation.
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