Unpaired Kidney Exchange: Overcoming Double Coincidence of Wants without Money

Speaker
Olivier Tercieux
Date
22/06/2021 - 12:45 - 11:45Add To Calendar 2021-06-22 11:45:31 2021-06-22 12:45:00 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. Location: https://us02web.zoom.us/j/82536086839 אוניברסיטת בר-אילן - Department of Economics Economics.Dept@mail.biu.ac.il Asia/Jerusalem public
Place
Location: https://us02web.zoom.us/j/82536086839
Affiliation
Paris School of Economics
Abstract

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.

Last Updated Date : 06/07/2021