Market Design

Name: Market Design | Auctions and Matching
Brand: MIT Press
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Auctions and Matching

Guillaume Haeringer(Autor*in)

MIT Press

Erschienen am 2. März 2018

392 Seiten

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Inhalt

Intro
Title Page
Copyright
Dedication
Table of Contents
Preface
1. Introduction
1.1. Market and Market Design
1.2. Do We Necessarily Have Prices?
1.3. More on Markets
1.3.1. What a Market Needs to Work
1.3.2. Commodities
1.4. Market Design: First Example
1.4.1. Feeding America
1.4.2. The First Design
1.4.3. The Problems .
1.4.4. . and a Solution
1.4.5. Results
2. Simple Auctions
2.1. Introduction
2.1.1. Auctions: A Definition
2.1.2. Auctions Are Everywhere
2.2. Valuations
2.3. Payoffs and Objectives
2.4. Ascending Auctions
2.4.1. The English Auctions
2.4.2. Bids, Strategies, and Payoffs in the English Auctions
2.4.3. Ticking Price
2.4.4. Truthful Bidding
2.5. Second-Price Auction
2.5.1. The Essence of the English Auction
2.5.2. The Vickrey Auction
2.5.3. English versus Second-Price Auctions
2.6. First-Price Auction
2.6.1. Definition
2.6.2. Optimal Bids in the First-Price Auction
2.6.3. Dutch Auction
2.7. Revenue Equivalence
2.8. Reserve Price
2.8.1. Optimal Reserve Price
2.8.2. Reserve Price versus Adding More Bidders
3. An Analysis of eBay
3.1. Introduction
3.2. eBay in Detail
3.2.1. Proxy Bidding
3.2.2. Bids and Bid Increments
3.2.3. Updating Rules
3.3. eBay as a First-Price Auction?
3.4. Bid Sniping
3.4.1. Amazon versus eBay
3.4.2. Data Analysis
3.5. Reserve Price
4. The Vickrey-Clarke-Groves Auction
4.1. Introduction
4.2. The Model
4.3. The VCG Auction
4.3.1. Computing the Optimal Assignment
4.3.2. Calculating Prices
4.4. Incentives under the VCG Auction
4.5. Relation with the Vickrey Auction
4.6. The Complexity of the VCG Auction
5. Keyword Auctions
5.1. Introduction
5.2. Running Billions and Billions of Auctions
5.3. The Origins
5.3.1. Payoff Flows
5.4. The Google Model: Generalized Second-Price Auction
5.4.1. Quality Scores
5.4.2. Truthtelling under the GSP Auction
5.4.3. Equilibrium under the GSP Auction
5.4.4. Assumptions about the Long-Run Equilibria
5.4.5. Refinement: Envy-Free Equilibrium
5.4.6. The Generalized English Auction
5.5. The Facebook Model: VCG for Internet Ads
5.5.1. Comparing VCG and GSP Auctions
5.5.2. The Rationale for VCG
6. Spectrum Auctions
6.1. How Can Spectrum Be Allocated?
6.1.1. Lotteries
6.1.2. Beauty Contests
6.1.3. Why Run Auctions?
6.2. Issues
6.2.1. General Issues
6.2.2. Collusion, Demand Reduction, and Entry
6.2.3. Maximum Revenue
6.2.4. The Exposure Problem
6.2.5. Winner's Curse
6.3. The Simultaneous Ascending Auction
6.4. Case Studies
6.4.1. The U.S. 1994 PCS Broadband Auction
6.4.2. Mistakes
7. Financial Markets
7.1. Introduction
7.2. Treasury Auctions
7.2.1. Outline
7.2.2. How Treasury Auctions Work
7.2.3. Analysis
7.3. Double Auctions
7.4. Initial Public Offering
7.4.1. Allocation and Pricing through Contracts
7.4.2. Auctions for IPOs
8. Trading
8.1. Stock Markets
8.2. Opening and Closing
8.3. High-Frequency Trading
8.3.1. Market Structure
8.3.2. Market Regulation
8.3.3. Surfing on the Latency
8.3.4. What Is the Matter with High Frequencies?
8.3.5. A Flawed Market Design?
8.4. Alternative Market Designs
8.4.1. Slowing Down Markets?
8.4.2. Frequent Batch Auctions
9. The Basic Matching Model
9.1. The Basic Matching Model
9.1.1. Preferences
9.1.2. Matching
9.1.3. Stability
9.2. Algorithms and Mechanisms
9.2.1. Algorithms?
9.2.2. Matching Mechanism
9.3. Finding Stable Matchings
9.3.1. The Deferred Acceptance Algorithm
9.3.2. Deferred Acceptance and Stable Matchings
9.4. Preferences Over Stable Matchings
9.4.1. Musician-Optimal and Singer-Optimal Matchings
9.4.2. Proofs
9.5. Incentives with the Deferred Acceptance Algorithm
10. The Medical Match
10.1. History
10.2. The Many-to-One Matching Model
10.2.1. Preferences in the Many-to-One Matching Model
10.2.2. Matchings and Stability in a Many-to-One Matching Model
10.2.3. Finding Stable Matchings
10.2.4. One-to-One v. Many-to-One Matchings: Similarities and Differences
10.3. Why Stability Matters
10.3.1. A Natural Experiment
10.3.2. Unraveling in the Lab
10.4. The Rural Hospital Theorem
10.5. The Case of Couples and the Engineering Method
10.5.1. A Very Complex Problem
10.5.2. When Theory Fails
10.5.3. Fixing the NRMP
11. Assignment Problems
11.1. The Basic Model
11.1.1. Public versus Private Endowments
11.1.2. Evaluating Assignments
11.2. Finding Efficient Assignments
11.2.1. Serial Dictators
11.2.2. Trading Cycles
11.2.3. Implementing Allocation Rules
11.2.4. Individual Rationality and the Core
11.3. Mixed Public-Private Endowments
11.3.1. Inefficient Mechanisms
11.3.2. Two Efficient Solutions
12. Probabilistic Assignments
12.1. Random Assignments
12.1.1. Preliminaries
12.1.2. The Birkhoff-von Neumann Theorem
12.1.3. Evaluating Random Assignments
12.2. Random Serial Dictatorship
12.3. The Probabilistic Serial Mechanism
13. School Choice
13.1. The Many-to-One Assignment Model
13.1.1. Preferences versus Priorities
13.1.2. The Model
13.1.3. Assignments
13.1.4. Stability and Efficiency
13.2. Competing Algorithms
13.2.1. The Role of Each Side of the Market
13.2.2. The Deferred Acceptance Algorithm
13.2.3. The Immediate Acceptance Algorithm
13.2.4. Top Trading Cycles
13.3. The Problem with the Immediate Acceptance Algorithm
13.4. Applications
13.4.1. The Boston School Match
13.4.2. The New York City School Match
14. School Choice: Further Developments
14.1. Weak Priorities
14.1.1. The Problem
14.1.2. Efficiency Loss
14.1.3. The Student-Optimal Assignment with Weak Priorities
14.1.4. Restoring Efficiency
14.1.5. How to Break Ties If You Must
14.2. Constrained Choice
14.2.1. Issues
14.2.2. From Very Manipulable to Less Manipulable
15. Course Allocation
15.1. Preliminaries
15.2. Bidding for Courses
15.2.1. The Bidding and Allocation Process
15.2.2. Issues: Nonmarket Prices and Inefficiency
15.2.3. Deferred Acceptance with Bids
15.3. The Harvard Business School Method
15.3.1. The Harvard Draft Mechanism
15.3.2. Strategic Behavior
15.3.3. Welfare
15.4. The Wharton Method
15.4.1. Approximate Competitive Equilibrium from Equal Incomes
15.4.2. The Wharton Experiment
16. Kidney Exchange
16.1. Background
16.2. Trading Kidneys
16.2.1. Trades versus Waiting List
16.2.2. The Kidney Exchange Algorithm
16.2.3. Chain Selection Rules
16.2.4. Efficiency and Incentives
16.3. On the Number of Exchanges
Appendix A: Game Theory
A.1. Strategic Form Games
A.1.1. Definition
A.1.2. Pure and Mixed Strategies
A.2. Extensive Form Games
A.2.1. Definition
A.2.2. Strategies
A.2.3. Imperfect Information
A.3. Solving Games
A.3.1. Dominated and Dominant Strategies
A.3.2. Elimination of Dominated Strategies
A.3.3. Nash Equilibrium
A.4. Bayesian Games: Games with Incomplete Information
A.4.1. Introductory Example
A.4.2. Definition
Appendix B: Mechanism Design
B.1. Preliminaries
B.2. The Model
B.2.1. Mechanism
B.2.2. Implementing Social Choice Functions
B.2.3. Direct versus Indirect Mechanism
B.3. Dominant Strategy Implementation
B.3.1. The Revelation Principle
B.3.2. The Gibbard-Satterthwaite Theorem
B.3.3. The Vickrey-Clarke-Groves Mechanism
B.4. Bayesian Mechanism Design
B.4.1. Bayesian Incentive Compatibility
B.4.2. Trading: The Myerson-Satterthwaite Theorem
Appendix C: Order Statistics
C.1. Expected Highest Valuation
C.1.1. Obtaining the Cumulative Density Function
C.1.2. Obtaining the Probability Density Function
C.1.3. Calculate the Expectation
C.2. Expected Second-Highest Valuation
C.3. Conditional Expectation of the Highest Valuation
C.4. Changing the Upper and Lower Bounds
References
Index

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