Matching Markets are the Future of Kidney Transplant
https://qz.com/421547/nobel-prize-winner-alvin-roth-explains-the-hidden-economics-behind-tinder-marriage-and-college-admissions/
This article details an interview with Nobel Prize recipient Alvin Roth, the economist mastermind behind one of the first kidney exchange clearinghouses in the nation. Organ donation, and kidney donation in particular, is a constantly failing system; for example, there are 100,000 Americans in need of a kidney, but the transplant rate is only 17,000 per year. Roth’s projected solution to this crisis, or at least his plan to ameliorate it slightly, is to create an altruistic kidney exchange chain: in effect, his ambition is to make a matching market. In the kidney business, it is clear that supply does not equal demand. If it did, there would be no issues, no need for a black market, and no waiting lists. This imbalance likely has proliferated because of the lack of incentivization for people to donate; kidneys are required by law, according to Roth, to be free gifts exchanged between mutually consenting adults. Additionally, there are strict social taboos around the ‘repugnant transaction’ of monetized organ exchange, making the market even more unappealing to potential donors. However, as Roth argues, if a system is developed which can efficiently incentivize and match donors to patients, this stalemate can very likely be diffused. Roth describes matching markets as those in which there are no zero-sum prices; that is, institutions like book publishers, labor markets, dating websites, and colleges value preference and compatibility, viewing many candidates and choosing those whom they are partial to. For example, Roth points out that corporations don’t gain employees by holding a Dutch auction for wages, lowering their standards until they reach a certain demographic. Instead, they hire based upon interview and resumé data, deciding upon those who seem the best fit for the company. This is precisely what Roth’s clearinghouses are intended to do; not everyone can expect to be on an active list at any given time, but through complex algorithms, donors, cadavers, and patients will be chosen based upon factors such as urgency and [most importantly] compatibility, and will be matched up immediately. With this altruistic kidney chain in motion, the battle against the transplant crisis can continue to be fought, and although Roth fears it is one we are losing, he hasn’t given up yet.
Roth’s work, as has been stated, is a clear example of a matching market, which is a system in which buyer preferences are revealed and influence the worth of the commodity at stake. One could, in fact, easily create a bipartite graph of a clearinghouse, with recipients on the right representing subjects and donor kidneys on the left as the product. Because they are biological entities, kidneys are very finicky when it comes to shelf life, blood type, and other risk factors, so they can certainly not be part of a regular commodity market in which prices and procedures are fixed and purchase is anonymous and random. This is where the matching market comes in; patients can input preferences for certain kidney traits, and the hope is that eventually a market-clearing scenario can be found in which each patient is matched to their kidney of preference. Of course, this system is not without setback; if, for example, two patient nodes are both compatible only with the same single kidney, a constricted set (a situation in which there are not enough products to satisfy all preferential customers) could form. In this instance, ‘prices’ on the over-desired kidney would need to be manipulated so that patients’ payoffs were altered and a perfect matching (one kidney per patient) could be achieved. In this instance, the social welfare of the graph would not be an answer to a homework problem, but instead the health of needy individuals whose lives depend on finding a perfect matching.
In a way, Roth’s work also fringes on game theory; for matching markets to be truly successful, especially in life-or-death situations like this one, donor and patient preferences must be truthful, fully disclosed, and goal-oriented. Therefore, one could call it the dominant strategy of matching market participants to be fully committed to finding a perfect matching. Because of the delicacy of transplants, perfect matchings should also occur in a reality where altering them would not make any patient better off. For example, if a patient receives a sub-par kidney because it was the only leftover, or two patients’ preferences and donors are swapped, there could be severe and even fatal consequences. Given this possibility, the clearinghouse situation must be the single best for all participants, who should all be content with their choices.