(eBook PDF) Market Design: Auctions and Matching (The MIT Press) – Digital Ebook – Instant Delivery Download
product details:
- ISBN-10 : 0262037548
- ISBN-13 : 978-0262037549
- Author: Guillaume Haeringer
A broad overview of market mechanisms, with an emphasis on the interplay between theory and real-life applications; examples range from eBay auctions to school choice.
This book offers an introduction to market design, providing students with a broad overview of issues related to the design and analysis of market mechanisms. It defines a market as a demand and a supply, without specifying a price system or mechanism. This allows the text to analyze a broad set of situations—including such unconventional markets as college admissions and organ donation—and forces readers to pay attention to details that might otherwise be overlooked. Students often complain that microeconomics is too abstract and disconnected from reality; the study of market design shows how theory can help solve existing, real-life problems. The book focuses on the interplay between theory and applications. To keep the text as accessible as possible, special effort has been made to minimize formal description of the models while emphasizing the intuitive, with detailed explanations and resolution of examples. Appendixes offer general reviews of elements of game theory and mechanism design that are related to the themes explored in the book, presenting the basic concepts with as many explanations and illustrations as possible.
table of contents:
1. Introduction
Part I. Microeconomic Fundamentals
2. Game-theoretical basics
3. Mechanism design
4. Single-object auctions
Part II. Multi-Object Auction Design
5. An overview of multi-object auctions;
6. The simultaneous multi-round auction format
7. Sealed-bid multi-object auctions
8. Open multi-object auctions
9. The combinatorial clock auction formats
Part III. Approximation and Matching Markets
10. Approximation mechanisms
11. Matching markets
12. Outlook
Part IV. Appendices: Mathematical Optimization
A. Linear optimization
B. Algorithms and complexity.
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