An Empirical Framework for Sequential Assignment: The Allocation of Deceased Donor Kidneys

Nikhil Agarwal, Itai Ashlagi, Michael Rees, Paulo Somaini and Daniel Waldinger
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Nikhil Agarwal: Department of Economics, MIT and NBER
Itai Ashlagi: Management Science and Engineering, Stanford U
Michael Rees: Department of Urology, University of Toledo Medical Center
Daniel Waldinger: Furman Center and Department of Economics, New York University

Research Papers from Stanford University, Graduate School of Business

Abstract: A transplant can improve a patient’s life while saving several hundreds of thousands of dollars in healthcare expenditures. Organs from deceased donors, like many other scarce public resources (e.g. public housing, child-care, publicly funded long-term care), are rationed via a sequential offer waiting list. The theoretical trade-offs in designing these mechanisms are not well understood and depend on agent preferences. This paper establishes an empirical framework for analyzing the trade-offs involved in designing sequential offer waiting lists and applies it to study the allocation of deceased donor kidneys. We model the decision to accept an organ while on the waiting list as an optimal stopping problem and use it to estimate the value of accepting various kidneys. Our estimates show that while some types of organs are preferable for all patients (e.g. organs from young donors), there is substantial match-specific heterogeneity in values. We show how to use these estimates to solve for the equilibria of counterfactual mechanisms. These techniques are then used to find mechanisms that improve on design goals such as improving the match quality of transplants and reducing organ waste.

Date: 2019-01
New Economics Papers: this item is included in nep-des
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