Online and Matching-based Market Design

The rich, multi-faceted and multi-disciplinary field of matching-based market design is an active and important one due to its highly successful applications with economic and sociological impact. Its home is economics, but with intimate connections to algorithm design and operations research. With chapters contributed by over fifty top researchers from all three disciplines, this volume is unique in its breadth and depth, while still being a cohesive and unified picture of the field, suitable for the uninitiated as well as the expert. It explains the dominant ideas from computer science and economics underlying the most important results on market design and introduces the main algorithmic questions and combinatorial structures. Methodologies and applications from both the pre-Internet and post-Internet eras are covered in detail. Key chapters discuss the basic notions of efficiency, fairness and incentives, and the way market design seeks solutions guided by normative criteria borrowed from social choice theory.

Federico Echenique is a Professor of Economics at the University of California at Berkeley. He has published articles in the American Economic Review, Econometrica, Journal of Political Economy, Quarterly Journal of Economics, Journal of Economic Theory, and Theoretical Economics. He is a fellow of the Econometric Society, and co-editor of Theoretical Economics. Echenique was Program Co-chair of EC 2021.

Nicole Immorlica is a Principal Researcher at the Microsoft Research New England Laboratory. She has published more than 80 scholarly articles, surveys, and book chapters on topics including algorithmic game theory, market design, social networks, theoretical computer science, and economics. Her honors include the Harvard Excellence in Teaching Award, a Sloan Fellowship, and an NSF Career Award. Immorlica is Chair of SIGecom, former Vice Chair of SIGACT, Associate Editor of ACM Transactions on Economics and Computing, and was Program Co-chair for EC 2019.

Vijay V. Vazirani is Distinguished Professor in the Computer Science Department at the University of California, Irvine. He is one of the founders of algorithmic game theory, focusing on the computability of market equilibria. He is an ACM Fellow, a Guggenheim Fellow, and the recipient of the 2022 INFORMS John von Neumann Theory Prize. His previous books include Approximation Algorithms and (co-edited) Algorithmic Game Theory.