Unpaired Kidney Exchange: Overcoming Double Coincidence of Wants without Money
Joint with: Mohammad Akbarpour, Julien Combe, Yinghua He, Victor Hiller, and Robert Shimer.
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. Our proposal, the Unpaired kidney exchange algorithm,
uses “memory” as a medium of exchange to eliminate these timing constraints. In a dynamic
matching model, we prove that Unpaired delivers a waiting time of patients close to optimal and
substantially shorter than currently utilized state-of-the-art algorithms. Using a rich administrative dataset from France, we show that Unpaired achieves a match rate of 57 percent and an
average waiting time of 440 days. The (infeasible) optimal algorithm is only slightly better (58
percent and 425 days); state-of-the-art algorithms deliver less than 34 percent and more than
695 days. We draw similar conclusions from the simulations of two large U.S. platforms. Lastly,
we propose a range of solutions that can address the potential practical concerns of Unpaired.
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תאריך עדכון אחרון : 06/07/2021