Unpaired Kidney Exchange: Overcoming Double Coincidence of Wants without Money

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.