Working Paper: NBER ID: w28064
Authors: Nikhil Agarwal; Charles Hodgson; Paulo Somaini
Abstract: While the mechanism design paradigm emphasizes notions of efficiency based on agent preferences, policymakers often focus on alternative objectives. School districts emphasize educational achievement, and transplantation communities focus on patient survival. It is unclear whether choice-based mechanisms perform well when assessed based on these outcomes. This paper evaluates the assignment mechanism for allocating deceased donor kidneys on the basis of patient life-years from transplantation (LYFT). We examine the role of choice in increasing LYFT and compare equilibrium assignments to benchmarks that remove choice. Our model combines choices and outcomes in order to study how selection affects LYFT. We show how to identify and estimate the model using instruments derived from the mechanism. The estimates suggest that the design in use selects patients with better post-transplant survival prospects and matches them well, resulting in an average LYFT of 8.78, which is 0.92 years more than a random assignment. However, the maximum aggregate LYFT is 13.84. Realizing the majority of the gains requires transplanting relatively healthy patients, who would have longer life expectancies even without a transplant. Therefore, a policymaker faces a dilemma between transplanting patients who are sicker and those for whom life will be extended the longest.
Keywords: assignment mechanisms; deceased donor kidneys; patient survival; life-years from transplantation
JEL Codes: C36; D47; I14
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
Cause | Effect |
---|---|
assignment mechanism for allocating deceased donor kidneys (D64) | average LYFT of 8.78 years (J17) |
assignment mechanism for allocating deceased donor kidneys (D64) | improved survival outcomes (I14) |
optimizing the allocation process (D61) | maximum aggregate LYFT of 13.84 years (J17) |
choice-based mechanism (D71) | higher LYFT than random allocation (C92) |