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Efficient Matching under Distributional Constraints: Theory and Applications
Author(s) -
Yuichiro Kamada,
Fuhito Kojima
Publication year - 2015
Publication title -
american economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.936
H-Index - 297
eISSN - 1944-7981
pISSN - 0002-8282
DOI - 10.1257/aer.20101552
Subject(s) - inefficiency , matching (statistics) , economics , incentive , market failure , microeconomics , stability (learning theory) , computer science , mathematical optimization , mathematics , machine learning , statistics
Many real matching markets are subject to distributional constraints. These constraints often take the form of restrictions on the numbers of agents on one side of the market matched to certain subsets on the other side. Real-life examples include restrictions on regions in medical matching, academic master's programs in graduate admission, and state-financed seats for college admission. Motivated by these markets, we study design of matching mechanisms under distributional constraints. We show that existing matching mechanisms suffer from inefficiency and instability, and propose a mechanism that is better in terms of efficiency, stability, and incentives while respecting the distributional constraints. (JEL C70, D61, D63)

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