Matching Markets in Kidney Exchange
In 2015, Matt Philips used Tinder, marriage, and college admissions to discuss the many relatable real-world examples of matching markets that exist and are part of our daily life. These matching markets govern decisions such as hiring a person, admitting a student, marrying your spouse and they also obey laws more complex than the simple balancing of supply and demand prices, which is seen in commodity markets. This article further discusses the algorithim that Alvin Roth, an economist, described the algorithim to create matchings in kidney exchange, rendering it another important example of matching market. Finally, the article discuses why the kidney exchange does not require monetary transaction explicitly between the patient and the donor.
In class we discussed matching markets to model the network structure and behavior of agents as they interact with each other. These matching markets elucidate three main principles, the effect of having different preferences for different kinds of products/services, the way prices can decentralize the allocation of goods to people, and the way these prices can lead to allocations that are socially optimal. In this article, different matching markets where discussed, I would like to focus on the kidney exchange example. The kidney exchange matching market highlights the issue that arises because many people suffer from kidney failure and require a kidney transplant. In some situations, a family member decides to donate one of their kidneys to a loved one, but in many situations, their kidneys are not compatible, implying that the donor’s kidney is unlikely to function well in the patient. As a result of the imbalance between the number of people waiting for kidney transplant and available donors (living and deceased), transplant centers must rely on altruistic act of people donating their kidney to random strangers in need. This altruistic act will be very remarkable and sometimes unlikley, but it is necessary in order to establish matches between donors and patients in a constitutive manner that does not subject patients to wait for years and living through the aid of dialysis.
Additionally, it is important to note that this matching market does cannot use price (in terms of money) to create socially optimal allocations because of the many different laws in place that prevent the sale of organs. Out of curiosity, how would allocation differ if patients were able to purchase kidneys from donors. I think that this would create a hierarchy of which kidneys the patient values most before the consideration of whether the kidney is compatible. Additionally, there would be an increase in the number of donors because there now exists a more appealing incentive to join the market other than simply altruism and wanting to help people. Overall, this market will no longer embrace some level of anonymity that once existed before with a third-party algorithm deciding the allocations, rather it will be more competition focused. In this situation, the donors will essentially keep increasing their prices until the market clears with allocations that are socially optimal. Finally, it is possible that socioeconomic disparities amongst patients will become an important factor in the matching market.