Unpaired Kidney Exchange: Overcoming Double Coincidence of Wants without Money

Joint with: Mohammad Akbarpour, Julien Combe, Yinghua He, Victor Hiller, and Robert Shimer.

Link to paper: https://drive.google.com/file/d/1oUV2SjhztblgFKq5W3KBH9bh5vYf1f7f/view

  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.

To view the seminar recording, click here.