Online and Matching-Based Market Design

Name: Online and Matching-Based Market Design
Brand: Cambridge University Press
Price: 72.49 EUR
Availability: OnlineOnly

Federico Echenique Nicole Immorlica Vijay V. Vazirani(Herausgeber*in)

Cambridge University Press

Erschienen am 7. Juni 2023

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Beschreibung

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.

Rezensionen / Stimmen

'This superb compendium of all aspects of matching markets is an excellent text for advanced students and a definitive reference that integrates economic and computational aspects of market design.' Robert Wilson, The Adams Distinguished Professor of Management, Emeritus, Stanford University 'Matching markets are among the earliest points of contact between the theories of economics and computation. Decades before the advent of Algorithmic Game Theory, great economists articulated discrete algorithmic problems involving agents, goods, and preferences, and invented efficient algorithms for their solution. In the era of the Internet, the importance of the subject has exploded, and so has the convergence of computational and economic research on it. This comprehensive collection of expertly written articles exhausting the many facets of this important topic is destined to influence its further evolution, and will be a quintessential source for students and researchers.' Christos H. Papadimitriou, Donovan Family Professor of Computer Science, Columbia University 'A multi-authored textbook is a challenging project, all the more so on a deeply interdisciplinary topic. Starting from the mathematical foundations and developing into sophisticated applications and empirics, all along supplemented by a rich menu of exercises, this volume makes the state of the art of market design equally accessible to the beginner students and advanced researchers.' Herve Moulin, The Donald J Robertson Professor of Economics, University of Glasgow 'The modern digital economy depends crucially on the performance of matching-based markets for goods and services ranging from energy to healthcare to cloud services and beyond. So it is wonderful to have a book that develops the beautiful and rich algorithmic and game theoretic foundations of these markets, taking us all the way to the research frontier. I can't wait to teach a course on online and matching-based market design based on this book!' Anna Karlin, Professor and Bill and Melinda Gates Chair of Computer Science and Engineering, University of Washington 'The definitive handbook for a beautiful scientific area that combines elegant theory with a variety of practical applications, economics with computer science, and classical results with fierce ongoing research.' Noam Nisan, Professor of Computer Science and Engineering, Hebrew University of Jerusalem

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Inhalt

Preface; Foreword Alvin E. Roth; Part I. Foundations of Market Design: 1. Two-sided markets: stable matching Federico Echenique, Nicole Immorlica and Vijay V. Vazirani; 2. One-sided matching markets Federico Echenique, Nicole Immorlica and Vijay V.Vazirani; 3. Matching markets with transfers and salaries Federico Echenique, Nicole Immorlica and Vijay V. Vazirani; 4. Objectives Federico Echenique, Nicole Immorlica and Vijay V.Vazirani; 5. Applications of online matching Zhiyi Huang and Thorben Trobst; 6. Online matching in advertisement auctions Nikhil R. Devanur and Aranyak Mehta; 7. Spectrum auctions from the perspective of matching Paul Milgrom and Andrew Vogt; 8. School choice Atila Abdulkadiroglu and Aram Grigoryam; 9. Kidney exchange Itai Ashlagi; 10. Normative properties for object allocation problems: characterizations and trade-offs Lars Ehlers and Bettina Klaus; 11. Choice and market design Samson Alva and Battal Dogan; 12. Combinatorics of stable matchings Tamas Fleiner; 13. Algorithmics of matching markets Jiehua Chen and David Manlove; 14. Generalized matching: contracts and networks John William Hatfield, Ravi Jagadeesan, Scott Duke Kominers, Alexandru Nichifor, Michael Ostrovsky, Alexander Teytelboym and Alexander Westkamp; 15. Complementarities and externalities Thanh Nguyen and Rakesh Vohra; 16. Large matching markets Jacob D. Leshno; 17. Pseudomarkets Marek Pycia; 18. Dynamic matching Mariagiovanna Baccara and Leeat Yariv; 19. Matching with search frictions Hector Chade and Philipp Kircher; 20. Unraveling Hanna Halaburda and Guillaume Haeringer; 21. Investment in matching markets Matthew Elliott and Eduard Talamas; 22. Signaling in two-sided matching markets Soohyung Lee; 23. Two-sided markets matching design Renato Gomez and Alessandro Pavan; 24. Matching market experiments Yan Chen; 25. Empirical models of non-transferable utility matching Nikhil Agarwal and Paulo Somaini; 26. Structural estimation of matching markets with transferable utility Alfred Galichon and Bernard Salanie; 27. New solution concepts Shengwu Li and Irene Lo; 28. Machine learning for matching markets Zhe Feng, David C. Parkes and Sai Srivatsa Ravindranath; 29. Contract theory Gabriel Carroll; 30. Secretaries, prophets, and applications to matching Michal Feldman and Brendan Lucier; 31. Exploration and persuasion Aleksandrs Slivkins; 32. Fairness in prediction and allocation Jamie Morgenstern and Aaron L. Roth.

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