Working Paper: NBER ID: w27765
Authors: Mohammad Akbarpour; Julien Combe; Yinghua He; Victor Hiller; Robert Shimer; Olivier Tercieux
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. Our proposed algorithm, 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.
Keywords: kidney exchange; unpaired exchange; double coincidence of wants; market design
JEL Codes: C78; D47; E49
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| unpaired algorithm design (C78) | average waiting times (C41) |
| unpaired algorithm (C69) | average waiting times (compared to pairwise algorithm) (C69) |
| unpaired algorithm (C69) | match rate (compared to pairwise algorithm) (C52) |
| unpaired algorithm (C69) | average waiting times (compared to chain algorithm) (C69) |
| unpaired algorithm (C69) | match rate (compared to chain algorithm) (C52) |
| optimal algorithm design (C61) | average waiting times (C41) |