市場設計入門:オークションとマッチング<br>Market Design : Auctions and Matching

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市場設計入門:オークションとマッチング
Market Design : Auctions and Matching

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  • 製本 Hardcover:ハードカバー版/ページ数 373 p.
  • 言語 ENG
  • 商品コード 9780262037549
  • DDC分類 381.1

Full Description


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.The book covers topics including the basics of simple auctions; eBay auctions; Vickrey-Clarke-Groves auctions; keyword auctions, with examples from Google and Facebook; spectrum auctions; financial markets, with discussions of treasury auctions and IPOs; trading on the stock market; the basic matching model; medical match; assignment problems; probabilistic assignments; school choice; course allocation, with examples from Harvard and Wharton; and kidney exchange.

Table of Contents

Preface                                            xv
1 Introduction 1 (12)
1.1 Market and Market Design 1 (1)
1.2 Do We Necessarily Have Prices? 2 (1)
1.3 More on Markets 3 (3)
1.3.1 What a Market Needs to Work 4 (1)
1.3.2 Commodities 5 (1)
1.4 Market Design: First Example 6 (7)
1.4.1 Feeding America 6 (1)
1.4.2 The First Design 7 (2)
1.4.3 The Problems... 9 (1)
1.4.4 ...And a Solution 10 (1)
1.4.5 Results 11 (2)
2 Simple Auctions 13 (36)
2.1 Introduction 13 (3)
2.1.1 Auctions: A Definition 14 (1)
2.1.2 Auctions Are Everywhere 14 (2)
2.2 Valuations 16 (1)
2.3 Payoffs and Objectives 17 (1)
2.4 Ascending Auctions 18 (7)
2.4.1 The English Auctions 18 (3)
2.4.2 Bids, Strategies, and Payoffs in 21 (1)
the English Auctions
2.4.3 Ticking Price 22 (1)
2.4.4 Truthful Bidding 23 (2)
2.5 Second-Price Auction 25 (4)
2.5.1 The Essence of the English Auction 25 (1)
2.5.2 The Vickrey Auction 26 (2)
2.5.3 English versus Second-Price 28 (1)
Auctions
2.6 First-Price Auction 29 (7)
2.6.1 Definition 29 (1)
2.6.2 Optimal Bids in the First-Price 30 (4)
Auction
2.6.3 Dutch Auction 34 (2)
2.7 Revenue Equivalence 36 (4)
2.8 Reserve Price 40 (9)
2.8.1 Optimal Reserve Price 42 (3)
2.8.2 Reserve Price versus Adding More 45 (4)
Bidders
3 An Analysis of eBay 49 (12)
3.1 Introduction 49 (1)
3.2 eBay in Detail 50 (4)
3.2.1 Proxy Bidding 50 (1)
3.2.2 Bids and Bid Increments 51 (1)
3.2.3 Updating Rules 51 (3)
3.3 eBay as a First-Price Auction? 54 (1)
3.4 Bid Sniping 54 (5)
3.4.1 Amazon versus eBay 55 (1)
3.4.2 Data Analysis 56 (3)
3.5 Reserve Price 59 (2)
4 The Vickrey-Clarke-Groves Auction 61 (10)
4.1 Introduction 61 (1)
4.2 The Model 61 (2)
4.3 The VCG Auction 63 (4)
4.3.1 Computing the Optimal Assignment 63 (3)
4.3.2 Calculating Prices 66 (1)
4.4 Incentives under the VCG Auction 67 (1)
4.5 Relation with the Vickrey Auction 68 (1)
4.6 The Complexity of the VCG Auction 69 (2)
5 Keyword Auctions 71 (24)
5.1 Introduction 71 (2)
5.2 Running Billions and Billions of 73 (1)
Auctions
5.3 The Origins 74 (2)
5.3.1 Payoff Flows 75 (1)
5.4 The Google Model: Generalized 76 (15)
Second-Price Auction
5.4.1 Quality Scores 76 (2)
5.4.2 Truthtelling under the GSP Auction 78 (1)
5.4.3 Equilibrium under the GSP Auction 78 (1)
5.4.4 Assumptions about the Long-Run 79 (1)
Equilibria
5.4.5 Refinement: Envy-Free Equilibrium 79 (9)
5.4.6 The Generalized English Auction 88 (3)
5.5 The Facebook Model: VCG for Internet 91 (4)
Ads
5.5.1 Comparing VCG and GSP Auctions 91 (3)
5.5.2 The Rationale for VCG 94 (1)
6 Spectrum Auctions 95 (18)
6.1 How Can Spectrum Be Allocated? 95 (3)
6.1.1 Lotteries 95 (1)
6.1.2 Beauty Contests 96 (1)
6.1.3 Why Run Auctions? 97 (1)
6.2 Issues 98 (6)
6.2.1 General Issues 98 (1)
6.2.2 Collusion, Demand Reduction, and 99 (2)
Entry
6.2.3 Maximum Revenue 101(1)
6.2.4 The Exposure Problem 102(1)
6.2.5 Winner's Curse 103(1)
6.3 The Simultaneous Ascending Auction 104(2)
6.4 Case Studies 106(7)
6.4.1 The U.S. 1994 PCS Broadband 106(3)
Auction
6.4.2 Mistakes 109(4)
7 Financial Markets 113(14)
7.1 Introduction 113(1)
7.2 Treasury Auctions 113(6)
7.2.1 Outline 113(2)
7.2.2 How Treasury Auctions Work 115(3)
7.2.3 Analysis 118(1)
7.3 Double Auctions 119(4)
7.4 Initial Public Offering 123(4)
7.4.1 Allocation and Pricing through 124(1)
Contracts
7.4.2 Auctions for IPOs 124(3)
8 Trading 127(22)
8.1 Stock Markets 127(5)
8.2 Opening and Closing 132(3)
8.3 High-Frequency Trading 135(10)
8.3.1 Market Structure 135(2)
8.3.2 Market Regulation 137(2)
8.3.3 Surfing on the Latency 139(2)
8.3.4 What Is the Matter with High 141(2)
Frequencies?
8.3.5 A Flawed Market Design? 143(2)
8.4 Alternative Market Designs 145(4)
8.4.1 Slowing Down Markets? 145(2)
8.4.2 Frequent Batch Auctions 147(2)
9 The Basic Matching Model 149(24)
9.1 The Basic Matching Model 149(7)
9.1.1 Preferences 150(2)
9.1.2 Matching 152(1)
9.1.3 Stability 153(3)
9.2 Algorithms and Mechanisms 156(3)
9.2.1 Algorithms? 156(3)
9.2.2 Matching Mechanism 159(1)
9.3 Finding Stable Matchings 159(5)
9.3.1 The Deferred Acceptance Algorithm 160(2)
9.3.2 Deferred Acceptance and Stable 162(2)
Matchings
9.4 Preferences Over Stable Matchings 164(3)
9.4.1 Musician-Optimal and 164(1)
Singer-Optimal Matchings
9.4.2 Proofs 165(2)
9.5 Incentives with the Deferred 167(6)
Acceptance Algorithm
10 The Medical Match 173(24)
10.1 History 173(2)
10.2 The Many-to-One Matching Model 175(11)
10.2.1 Preferences in the Many-to-One 176(3)
Matching Model
10.2.2 Matchings and Stability in a 179(3)
Many-to-One Matching Model
10.2.3 Finding Stable Matchings 182(2)
10.2.4 One-to-One v. Many-to-One 184(2)
Matchings: Similarities and Differences
10.3 Why Stability Matters 186(4)
10.3.1 A Natural Experiment 186(1)
10.3.2 Unraveling in the Lab 187(3)
10.4 The Rural Hospital Theorem 190(2)
10.5 The Case of Couples and the 192(5)
Engineering Method
10.5.1 A Very Complex Problem 192(1)
10.5.2 When Theory Fails 193(1)
10.5.3 Fixing the NRMP 194(3)
11 Assignment Problems 197(26)
11.1 The Basic Model 197(2)
11.1.1 Public versus Private Endowments 198(1)
11.1.2 Evaluating Assignments 198(1)
11.2 Finding Efficient Assignments 199(13)
11.2.1 Serial Dictators 199(1)
11.2.2 Trading Cycles 200(5)
11.2.3 Implementing Allocation Rules 205(5)
11.2.4 Individual Rationality and the 210(2)
Core
11.3 Mixed Public-Private Endowments 212(11)
11.3.1 Inefficient Mechanisms 213(4)
11.3.2 Two Efficient Solutions 217(6)
12 Probabilistic Assignments 223(16)
12.1 Random Assignments 223(6)
12.1.1 Preliminaries 223(2)
12.1.2 The Birkhoff--von Neumann Theorem 225(2)
12.1.3 Evaluating Random Assignments 227(2)
12.2 Random Serial Dictatorship 229(2)
12.3 The Probabilistic Serial Mechanism 231(8)
13 School Choice 239(24)
13.1 The Many-to-One Assignment Model 239(6)
13.1.1 Preferences versus Priorities 239(2)
13.1.2 The Model 241(1)
13.1.3 Assignments 241(1)
13.1.4 Stability and Efficiency 242(3)
13.2 Competing Algorithms 245(11)
13.2.1 The Role of Each Side of the 245(1)
Market
13.2.2 The Deferred Acceptance Algorithm 246(2)
13.2.3 The Immediate Acceptance 248(2)
Algorithm
13.2.4 Top Trading Cycles 250(6)
13.3 The Problem with the Immediate 256(1)
Acceptance Algorithm
13.4 Applications 257(6)
13.4.1 The Boston School Match 257(2)
13.4.2 The New York City School Match 259(4)
14 School Choice: Further Developments 263(20)
14.1 Weak Priorities 263(13)
14.1.1 The Problem 263(1)
14.1.2 Efficiency Loss 264(1)
14.1.3 The Student-Optimal Assignment 265(1)
with Weak Priorities
14.1.4 Restoring Efficiency 266(6)
14.1.5 How to Break Ties If You Must 272(4)
14.2 Constrained Choice 276(7)
14.2.1 Issues 277(2)
14.2.2 From Very Manipulable to Less 279(4)
Manipulable
15 Course Allocation 283(20)
15.1 Preliminaries 283(1)
15.2 Bidding for Courses 284(6)
15.2.1 The Bidding and Allocation 285(1)
Process
15.2.2 Issues: Nonmarket Prices and 286(2)
Inefficiency
15.2.3 Deferred Acceptance with Bids 288(2)
15.3 The Harvard Business School Method 290(5)
15.3.1 The Harvard Draft Mechanism 290(1)
15.3.2 Strategic Behavior 291(2)
15.3.3 Welfare 293(2)
15.4 The Wharton Method 295(8)
15.4.1 Approximate Competitive 296(2)
Equilibrium from Equal Incomes
15.4.2 The Wharton Experiment 298(5)
16 Kidney Exchange 303(14)
16.1 Background 303(2)
16.2 Trading Kidneys 305(8)
16.2.1 Trades versus Waiting List 306(1)
16.2.2 The Kidney Exchange Algorithm 306(3)
16.2.3 Chain Selection Rules 309(2)
16.2.4 Efficiency and Incentives 311(2)
16.3 On the Number of Exchanges 313(4)
Appendix A Game Theory 317(18)
A.1 Strategic Form Games 317(2)
A.1.1 Definition 317(1)
A.1.2 Pure and Mixed Strategies 318(1)
A.2 Extensive Form Games 319(5)
A.2.1 Definition 320(1)
A.2.2 Strategies 321(1)
A.2.3 Imperfect Information 322(2)
A.3 Solving Games 324(6)
A.3.1 Dominated and Dominant Strategies 324(2)
A.3.2 Elimination of Dominated 326(2)
Strategies
A.3.3 Nash Equilibrium 328(2)
A.4 Bayesian Games: Games with Incomplete 330(5)
Information
A.4.1 Introductory Example 330(1)
A.4.2 Definition 331(4)
Appendix B Mechanism Design 335(14)
B.1 Preliminaries 335(2)
B.2 The Model 337(4)
B.2.1 Mechanism 337(2)
B.2.2 Implementing Social Choice 339(1)
Functions
B.2.3 Direct versus Indirect Mechanism 340(1)
B.3 Dominant Strategy Implementation 341(3)
B.3.1 The Revelation Principle 341(1)
B.3.2 The Gibbard-Satterthwaite Theorem 342(1)
B.3.3 The Vickrey-Clarke-Groves 343(1)
Mechanism
B.4 Bayesian Mechanism Design 344(5)
B.4.1 Bayesian Incentive Compatibility 344(1)
B.4.2 Trading: The 345(4)
Myerson-Satterthwaite Theorem
Appendix C Order Statistics 349(6)
C.1 Expected Highest Valuation 349(2)
C.1.1 Obtaining the Cumulative Density 350(1)
Function
C.1.2 Obtaining the Probability Density 350(1)
Function
C.1.3 Calculate the Expectation 350(1)
C.2 Expected Second-Highest Valuation 351(1)
C.3 Conditional Expectation of the 352(1)
Highest Valuation
C.4 Changing the Upper and Lower Bounds 353(2)
Notes 355(10)
References 365(4)
Index 369