集中式匹配市场中的优先级设计

Oğuzhan Çelebi, Joel P. Flynn
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引用次数: 8

摘要

在许多集中式匹配市场中,优先级采取底层顺序的单调转换形式。突出的例子包括波士顿公立学校采用的基于距离的系统,居住在步行区域内的学生优先于所有其他学生,以及纽约经济适用房分配中使用的基于收入的系统,其资格取决于收入的大幅削减。受此启发,我们研究了不逆转外生给定的潜在顺序的最优优先级设计。我们的主要结果是,在稳定的匹配机制下,最优设计可以通过将代理划分为最多三个对象特定的无差异类来实现。我们运用我们的框架,在三个应用程序中提供最佳优先级设计和追求优先级合理化的见解:波士顿公立学校的基于距离的优先级,芝加哥考试学校的入学考试,以及纽约公共住房分配的基于收入的优先级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Priority Design in Centralized Matching Markets
In many centralized matching markets, priorities take the form of a monotone transformation of an underlying order. Prominent examples include the distance-based system employed by Boston Public Schools, where students who lived within a walk-zone were prioritized over all others, and the income-based system used in New York affordable housing allocation, where eligibility is determined by a sharp income cutoff. Motivated by this, we study optimal priority design subject to not reversing an exogenously-given underlying order. Our main result is that, under stable matching mechanisms, the optimal design can be attained by splitting agents into at most three object-specific indifference classes. We apply our framework to provide insights into optimal priority design and rationalizations of the pursued priorities in three applications: distance-based priorities in Boston Public Schools, admissions tests for Chicago exam schools, and income-based priorities in New York public housing allocation.
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