Empirical Analysis of Resource Allocation Problems

资源配置问题的实证分析

• 批准号: 1729090
• 负责人: Nikhil Agarwal
• 金额: $ 25.03万
• 依托单位: National Bureau of Economic Research Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1729090&HistoricalAwards=false
• 关键词: Empirical; Analysis; Resource; Allocation; Problems

Approximately 100,000 patients are waiting for a life-saving kidney transplant, but only about 12,000 patients receive a transplant through the deceased donor waiting list in a typical year. Another 6,000 patients receive a live-donor kidney transplant. Given the scarcity of donors, it is important to find the best ways to organize organ allocation systems in the US. The investigator aims to use data driven methods to find better designs, promising savings on the costs of dialysis while simultaneously improving health outcomes. More broadly, this research is of interest to a growing body of empirical work studying how non-market mechanisms can be used to allocate scarce resources. This research studies both deceased and living donor kidney allocation systems. Priorities on the deceased donor list are determined by a variety of factors. Remarkably, most donor offers are turned down by several patients before their organs are ultimately transplanted because many patients prefer waiting for a better organ. The first project thus studies how to design the priorities and the allocation system to better align the system with objectives such as allocating organs to those that will get the most life-years from it. The second project on living donor kidney allocations studies the effects of hospital decisions to select which patients and donors are registered on nationwide kidney exchanges. This project uses data driven techniques and designs a well-tailored priority system that can align hospital incentives for participating in these platforms with social objectives. These projects complement and build on a recent body of theoretical work in economics that has studied how to allocate these scarce resources. Specifically, the investigator develops empirical approaches to study and evaluate dynamic allocation problems and barter exchanges. These techniques are likely to be useful in the study of a variety of other resource allocation problems including the allocation of public housing, child-care and child adoption in addition to organs of all types. The methods developed in this research present new approaches to topics studied by researchers in Operations Research, Health Economics, and Medical Transplantation.

大约有10万名患者正在等待挽救生命的肾移植，但在典型的一年中，只有大约12 000名患者通过已故捐赠者等待名单接受移植。另有6,000名患者接受了活体肾脏移植。鉴于捐献者的稀缺性，找到组织美国器官分配系统的最佳方法至关重要。研究人员的目标是使用数据驱动的方法来找到更好的设计，有望节省透析成本，同时改善健康结果。更广泛地说，这项研究是感兴趣的越来越多的实证工作，研究如何非市场机制可以用来配置稀缺资源。这项研究研究了已故和活体捐赠者肾脏分配系统。已故捐赠者名单上的优先顺序是由各种因素决定的。值得注意的是，大多数捐赠者在他们的器官最终被移植之前都会被几个病人拒绝，因为许多病人宁愿等待更好的器官。因此，第一个项目研究如何设计优先级和分配系统，以更好地使系统与目标保持一致，例如将器官分配给那些将从中获得最多生命年的人。第二个项目关于活体肾脏分配，研究医院决定选择哪些患者和捐赠者在全国肾脏交换中登记的影响。该项目使用数据驱动技术，并设计了一个量身定制的优先级系统，可以使医院参与这些平台的激励措施与社会目标保持一致。这些项目补充并建立在最近的经济学理论工作的基础上，这些理论工作研究了如何分配这些稀缺资源。具体来说，研究者开发的实证方法来研究和评估动态分配问题和易货交易。这些技术可能有助于研究各种其他资源分配问题，包括分配公共住房、儿童保育和儿童收养以及各种器官。在这项研究中开发的方法提出了新的方法研究课题的研究人员在运筹学，卫生经济学和医疗移植。

项目成果

Market Failure in Kidney Exchange

肾脏交换市场失灵

• DOI: 10.1257/aer.20180771
• 发表时间: 2019
• 期刊: American Economic Review
• 影响因子: 10.7
• 作者: Agarwal, Nikhil;Ashlagi, Itai;Azevedo, Eduardo;Featherstone, Clayton R.;Karaduman, Ömer
• 通讯作者: Karaduman, Ömer

Dynamic Incentives in Wait List Mechanisms

候补名单机制中的动态激励

• DOI: 10.1257/pandp.20181079
• 发表时间: 2018
• 期刊: AEA Papers and Proceedings
• 作者: Agarwal, Nikhil;Ashlagi, Itai;Somaini, Paulo;Waldinger, Daniel
• 通讯作者: Waldinger, Daniel