Matching Markets and Organ Transplants
http://web.stanford.edu/~alroth/AMNews_Jan.28,2008.pdf
Matching Markets are useful in theory, but in reality, the concept of perfect market matchings are sometimes not so easily applied. Specifically, the applications of Matching Market concepts on organ donations is often debated upon. In an article titled “Economists Study Says Paying for Organs Could Cut Wait Lists” by Kevin B. O’Reilly, it is stated that 100,000 Americans wait for organ donations every day, and 17 of them die while waiting. In terms of Market Matching, the present issue provided by this statistic is that the bipartite graph where there is an equal number of buyers and sellers likely does not exist. Hence, a perfect matching is certainly not possible because there will always be a constricted set in which more patients want organs from a smaller amount of donors. Thus, it was proposed that this problem could be solved by putting prices on the organs themselves so that the number of people who receive transplants could increase. In other words, there would ideally be a perfect-matching.
On the surface, this idea seems very promising since it is based upon the same conclusions of Market Matching––that putting prices on the items eventually yields a perfect matching in a bipartite graph. In this case, the buyers are those who need transplants and the sellers would be those who provide the organs. However, upon further thought, I found that the concepts of Market Matching as taught in class might not apply so well in this scenario.
As one example, it is predicted in the article that putting a $15,000 price on kidneys to donors would increase kidney transplants by around 44% a year at an estimated 200,000 transplants. This prediction is based upon the amount of money it would take to convince an American earning the median salary to donate their kidney. In terms of Market Matchings, this would mean creating more “sellers”. Yes, this would create the possibility of a bipartite buyer-seller graph, which is the first criteria needed for a perfect matching to exist. However, this proposal does not exactly emulate a Market Matching because all the kidneys would have the same price, whereas in a Market Matching scenario, the prices would continually raise at different rates until someone backs out and is willing to buy another item. Already, there is evidence of flaw in the application of Market Matching to organ transplants; the question of whether prices for kidneys should or could vary based on location, health of the donor, etc., is certainly ethically questionable as well. As for the kidney “buyers”, their values or how much they are willing to pay for the kidney would be based on how dire their situations are. Someone who has been waiting longer would have values that rise with time. Hence, the ability for values to increase means that even if prices for the kidneys were to increment, the buyer would not necessarily back out. Also, the market-clearing price is likely never going to be a flat 15,000, since in addition to patients’ fluid valuation of the kidneys, the number of patients and donors is always changing as well. The algorithm used to create perfect matchings in Market Matching is far too simple to be applied to such an ever-changing process. Thus, although the result and set-up of organ transplants is similar to that of the Market Matching model, there are some key differences and outside factors that suggest it is not so applicable.