Unpaired Kidney Exchange: Overcoming Double Coincidence of Wants without Money

Mohammad Akbarpour, Julien Combe (), Yinghua He, Victor Hiller (), Robert Shimer and Olivier Tercieux ()
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Mohammad Akbarpour: Stanford University
Julien Combe: CREST - Centre de Recherche en Economie et Statistique [Bruz] - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique
Yinghua He: Rice University [Houston]
Victor Hiller: LEMMA - Laboratoire d'économie mathématique et de microéconomie appliquée - Université Paris-Panthéon-Assas
Robert Shimer: University of Chicago
Olivier Tercieux: PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris

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Abstract: For an incompatible patient–donor pair, kidney exchanges often forbid receipt-before-donation (the patient receives a kidney before the donor donates) and donation-before-receipt, causing a double-coincidence-of-wants problem. We study an algorithm, the Unpaired kidney exchange algorithm, which eliminates this problem. In a dynamic matching model, we show that the waiting time of patients under Unpaired is close to optimal and substantially shorter than under widely used algorithms. Using a rich administrative dataset from France, we show that Unpaired achieves a match rate of 63% and an average waiting time of 176 days for transplanted patients. The (infeasible) optimal algorithm is only slightly better (64% and 144 days); widely used algorithms deliver less than 40% match rate and at least 232 days waiting times. We discuss a range of solutions that can address the potential practical incentive challenges of Unpaired. In particular, we extend our analysis to an environment where a deceased donor waitlist can be integrated to improve the performance of algorithms. We show that our theoretical and empirical comparisons continue to hold. Finally, based on these analyses, we propose a practical version of the Unpaired algorithm.

Date: 2025-07
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Published in Review of Economic Studies, 2025, 92 (4), pp.2108-2164. ⟨10.1093/restud/rdae081⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:pseptp:halshs-05845633

DOI: 10.1093/restud/rdae081

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