Matching and Markets
Many important economic allocation problems are resolved through centralized "matching markets," and economists are increasingly involved in the design and evaluation of such centralized markets. Applications range from labor markets (for example, the National Resident Matching Program, in medicine) to the allocation of students to public schools in large metropolitan areas to the design of efficient organ donation procedures. The unique interdisciplinary nature of Caltech's faculty allows us to combine experimental, theoretical, and empirical work to study a variety of questions: What outcomes should we expect from different matching processes, centralized or decentralized? When should market designers intervene and organize a centralized matching market? What can be deduced about the underlying features of the market's participants (in particular, their preferences) from market outcomes?
Caltech researchers have studied such varied applications as the "marriage market" in the United States, the design of markets that respect diversity and social policy objectives (for example, so-called "controlled school choice"), the American child adoption process, the assignment of colleagues into offices, and the formation of friendships among children in schools.
Methodologically, Caltech researchers have provided tools to understand the structure of market outcomes. As is often the case at Caltech, our research has proceeded with both new theory and experiments. Theoretical contributions provide an analytical framework for general matching markets and a methodology for understanding and optimizing, for example, controlled school choice—which presents the challenge of designing markets that meet certain compositional policy objectives. Caltech's strength in experimental methods has been key for validating, but also questioning, some of the commonly made assumptions in the theoretical analysis of matching markets. The most common solutions concepts find validation in the lab, but some of the conventional wisdom on how market participants behave does not.
The following are a sampling of publications in this field by scholars affiliated with CTESS:
- "Paying to Match: Decentralized Markets with Information Frictions" (2022) by Marina Agranov, Ahrash Dianat, Larry Samuelson, and Leeat Yariv.
- "Stable matching under forward-induction reasoning" (2022) by Luciano Pomatto, Theoretical Economics.