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集中匹配市场中的优先级设计

Priority Design in Centralized Matching Markets
Review of Economic Studies · 2021 · Oğuzhan Çelebi、Joel P. Flynn

中文摘要

在许多集中匹配市场中,代理人对物品的产权源自对基础分数的粗化处理。典型例子包括波士顿公立学校采用的基于距离的制度:对于每所学校,居住在该校一定半径内的学生优先于所有其他学生;以及纽约公共住房分配采用的基于收入的制度:申请资格由一个明确的收入门槛决定。受此启发,我们研究如何对基础分数进行最优粗化。我们的主要结果是,对于任意连续目标函数,在稳定匹配机制下,均可通过针对每个物品将代理人划分为至多三个无差异类来实现最优设计。我们通过三个应用来阐明这一设计问题:波士顿公立学校基于距离的分数、芝加哥考试招生学校基于考试的分数,以及纽约公共住房分配中基于收入的分数。

Abstract

Abstract In many centralized matching markets, agents’ property rights over objects are derived from a coarse transformation of an underlying score. Prominent examples include the distance-based system employed by Boston Public Schools, where students who lived within a certain radius of each school were prioritized over all others, and the income-based system used in New York public housing allocation, where eligibility is determined by a sharp income cutoff. Motivated by this, we study how to optimally coarsen an underlying score. Our main result is that, for any continuous objective function and under stable matching mechanisms, the optimal design can be attained by splitting agents into at most three indifference classes for each object. We provide insights into this design problem in three applications: distance-based scores in Boston Public Schools, test-based scores for Chicago exam schools, and income-based scores in New York public housing allocation.
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