EAGER: Algorithmic Approaches for Developing Markets

市场是将稀缺资源分配给个人、协调集体行为并决定社会结果的系统。对市场设计的研究影响了FCC频谱拍卖，国家居民匹配计划和学校选择计划等。 该项目的目标是使主要为贫穷和处境不利的参与者服务的所谓发展中市场取得类似的成果。该项目将使用两个不同的市场，每个市场都有自己的理论和实践挑战，作为本研究议程的例子。第一个是乌干达的农业市场。这个市场的目标是在自给农民和购买者之间找到一套有效的交易。第二个是泰国的保险市场。这个市场的目标是为村民建立一个借贷系统。除了改善世界各地受发展中市场影响的人们的生活外，该项目还将为研究生和本科生提供参与研究的机会，以及理论计算机科学家和发展经济学家之间丰富的跨学科互动。发展中市场对市场设计师提出了独特的挑战，并提供了一个机会，以促进国家的最先进的市场设计。主要的挑战是信息方面的：由于技术的限制，设计者对基本经济环境的了解和接触比通常假设的要少得多。这些市场中的人口往往迫切需要获得资本，同时也是高度短暂的。这两个因素都促使市场迅速出清。然而，这牺牲了市场厚度，从而降低了市场结果的质量。本项目考虑解决这一问题的技术，包括将市场参与者的随机假设纳入分配方案。第二个挑战是需要简单和透明。 考虑到这一点，可以理解的是，这些人口对外部干预持怀疑态度，并且无法获得帮助他们优化市场战略的技术，因此，本项目的机制将设计得易于理解和使用，包括将设计空间限制在最接近最优方案的一个机构子类上。这个奖项反映了NSF的法定使命，并被认为是值得支持的通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

Markets are systems that allocate scarce resources to individuals, coordinate aggregate behavior, and determine societal outcomes. Research on the design of markets has impacted the FCC spectrum auctions, the National Residency Matching Program, and school choice programs, among others. The goal of this project is to bring similar fruit to bear on so-called developing markets that primarily serve poor and disadvantaged participants. The project will use two distinct markets, each with their own theoretical and practical challenges, as examples of this research agenda. The first is an agricultural market in Uganda. The goal of this market is to find an efficient set of trades among subsistence farmers and buyers. The second is an insurance market in Thailand. The goal of this market is to build a system of lending and borrowing for villagers. In addition to improving the lives of those who are impacted by developing markets, found all over the world, the project will provide opportunities for graduate and undergraduate students to participate in the research, as well as a rich interdisciplinary interaction between theoretical computer scientists and development economists.Developing markets present unique challenges to a market designer, and present an opportunity to advance the state-of-the-art in market design. The primary challenge is an informational one: due to technological constraints, the designer has significantly less knowledge of and access to the underlying economic environment than is typically assumed. Populations in these markets often have urgent need for access to capital, while also being highly transitory. Both these factors push markets to clear rapidly. This, however, sacrifices market thickness and so degrades the quality of market outcomes. This project considers techniques to address this, including allocation schemes that incorporate stochastic assumptions about market participants. A secondary challenge concerns the need for simplicity and transparency. Given that, such populations are understandably suspicious of outside interventions, and lack access to technologies that help them optimize their strategies within a market, the mechanisms in this project will be designed to be easy to comprehend and easy to play, including restricting the design space to a subclass of mechanisms that closely approximate the optimal one.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.