Fraud-proof Mechanism Design

这项研究的重点是设计更好的合同和拍卖机制的背景下，代理人可以从事昂贵的（或危险的）欺诈。该项目扩展了机制设计理论（通常被认为是经济学的工程方面）。具体而言，这项工作提高了我们对公共住房单位、精选学校席位、人体器官和其他物品分配的理解，这些物品的分配没有货币转移，可能受到虚假申请的影响。资格通常基于一个分数（度量），该分数代表将单位分配给个人的社会价值。然而，对该指标的依赖产生了强烈的激励，导致伪造、漂绿、应试教育或操纵统计数据等做法司空见惯。臭名昭著的例子包括医生升级他们的病人的治疗，以增加他们在器官等待名单上的优先权，家庭使用假地址来进入理想的公立学校，以及在大学招生丑闻期间，富裕的父母以各种精心设计的方式帮助他们的孩子进入美国高度选择性的大学。对系统的游戏会导致分配不当，结果不公平，并侵蚀公众的信任。更擅长游戏的社会经济群体可以更快地获得器官移植，为他们的孩子安排更好的学校作业，等等。这种分配不当不仅不公平，而且在某些情况下还可能造成生命损失。研究人员开发了最大化分配效率的程序，同时防止欺诈，这意味着个人不能从游戏中获益。与大多数机制设计文献相反，这些文献假设误报是无成本的，该奖项资助的研究通过自然分数和其他私人已知的维度来描述代理人，他们可以付出代价来伪造（品味，游戏能力），他们可以歪曲没有成本。分析表明，如何利用伪造成本来设计最优分配程序。所开发的解决方法补充了源于Myerson（1981）的技术，这些技术已被广泛应用于有转移的设置，以及Amador等人（2006）和其他人在无转移设置中使用的拉格朗日技术。该研究计划提出了一种解决机制设计问题的开创性方法，而无需转移和昂贵的欺诈，突出了与最佳运输理论文献的新颖联系。在经济学中，它扩展了主要的机制设计范式，允许代理人的私人信息具有“硬”（误报成本高）和“软”（误报自由）维度。我们提供的设置和见解可以应用于评级系统的设计，联邦资金是根据该系统分配的（例如，医疗补助提供者和养老院的评级系统）。它们也可以应用于会计和税务标准的设计。所有这些系统都经常受到游戏和操纵的困扰，这使得我们的建模基于昂贵的类型伪造相关。该项目还对计算机科学产生了跨学科的影响。计算机科学理论涉及算法操作。考虑到这种操作可能是昂贵的，算法的抽象建模类似于没有传输的机制，建模和解决方案的方法可以应用到防操作算法的设计。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

This research focuses on designing better contracts and auction mechanisms in contexts where agents can engage in costly (or risky) fraud. The project extends the theory of mechanism design (which is often considered as the engineering side of economics.). Specifically, this work improves our understanding of the allocation of public housing units, seats in selective schools, human organs, and other goods whose assignments are done without monetary transfers and may be affected by falsified applications. Eligibility is usually based on a score (metric) that proxies the social value of assigning a unit to an individual. However, reliance on the metric creates strong incentives to game it. As a result, practices such as forgery, greenwashing, teaching to the test, or manipulating statistics are commonplace. Infamous examples include doctors escalating their patients' treatments to increase their priority on organ waiting lists, families using a fake address to gain access to a desirable public school, and the various elaborate ways well-off parents facilitated admissions of their children to highly selective universities in the US during the college admissions scandal. Gaming the system leads to misallocation, unfair outcomes, and erodes public trust. Socio-economic groups better at gaming achieve faster access to organ transplants, better school assignments for their children, and so forth. The misallocations are not only unfair but they can also cost lives in some cases. The researcher develops procedures that maximize allocative efficiency while being fraud-proof, meaning individuals cannot benefit from gaming their scores.In contrast to the majority of the mechanism design literature, which assumes that misreporting is costless, the research funded by this award characterizes agents by their natural score, which they can falsify at a cost, and by other privately-known dimensions (tastes, gaming abilities) that they can misrepresent at no cost. The analysis shows how one can leverage falsification costs to design optimal allocation procedures. The developed solution methodology complements techniques stemming from Myerson (1981), which have been widely applied to settings with transfers, as well as the Lagrangian techniques employed by Amador et al. (2006) and others for settings without transfers. The research program suggests a pioneering way of tackling problems of mechanism design without transfers and costly fraud, highlighting novel connections to the literature of optimal transportation theory. Within economics, it extends the main mechanism design paradigm by allowing agents' private information to have 'hard' (costly to misreport) and 'soft' (free to misreport) dimensions. The setting and insights we provide can be applied to the design of rating systems based on which federal funds are allocated (for example, rating systems for Medicaid providers and nursing homes). They can also be applied to the design of accounting and taxation standards. All these systems are often plagued by gaming and manipulations, making our modeling based on costly type falsification relevant. The project also has interdisciplinary impacts on computer science. Computer science theory is concerned with algorithmic manipulations. Given that such manipulations can be costly and that the abstract modeling of algorithms resembles that of mechanisms without transfers, the modeling and solution approach can be applied to the design of manipulation-proof algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.