Strategyproof Matching with Minimum Quotas

Author:

Fragiadakis Daniel1,Iwasaki Atsushi2,Troyan Peter3,Ueda Suguru4,Yokoo Makoto4

Affiliation:

1. Texas A&M University, College Station, TX

2. University of Electro-Communications, Tokyo, Japan

3. University of Virginia, Charlottesville, VA

4. Kyushu University, Fukuoka, Japan

Abstract

We study matching markets in which institutions may have minimum and maximum quotas. Minimum quotas are important in many settings, such as hospital residency matching, military cadet matching, and school choice, but current mechanisms are unable to accommodate them, leading to the use of ad hoc solutions. We introduce two new classes of strategyproof mechanisms that allow for minimum quotas as an explicit input and show that our mechanisms improve welfare relative to existing approaches. Because minimum quotas cause a theoretical incompatibility between standard fairness and nonwastefulness properties, we introduce new second-best axioms and show that they are satisfied by our mechanisms. Last, we use simulations to quantify (1) the magnitude of the potential efficiency gains from our mechanisms and (2) how far the resulting assignments are from the first-best definitions of fairness and nonwastefulness. Combining both the theoretical and simulation results, we argue that our mechanisms will improve the performance of matching markets with minimum quota constraints in practice.

Funder

JSPS Kakenhi

Stanford Institute for Economic Policy Research through the B.F. Haley and E.S. Shaw Fellowship

Leonard W. Ely

Shirley R. Ely Fellowship

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Mathematics,Marketing,Economics and Econometrics,Statistics and Probability,Computer Science (miscellaneous)

Cited by 57 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fair division with two-sided preferences;Games and Economic Behavior;2024-09

2. Stable Matching Based Revenue Maximization for Federated Learning in UAV-Assisted WBANs;IEEE Transactions on Services Computing;2024-07

3. Open RAN Slicing for MVNOs With Deep Reinforcement Learning;IEEE Internet of Things Journal;2024-05-15

4. Efficient matching under general constraints;Games and Economic Behavior;2024-05

5. "Smart University" project: fair matching of students to academic trajectories;Proceedings of Voronezh State University Series: Economics and management;2024-03-31

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3