A Review of Auction Theory: Sequential Auctions and Vickrey Auctions

Similar documents
Multi-object auctions (and matching with money)

Vickrey-Clarke-Groves Mechanisms

CPS 173 Mechanism design. Vincent Conitzer

Vickrey Auction. Mechanism Design. Algorithmic Game Theory. Alexander Skopalik Algorithmic Game Theory 2013 Mechanism Design

Solution: Since the prices are decreasing, we consider all the nested options {1,..., i}. Given such a set, the expected revenue is.

Game Theory: Spring 2017

University of Warwick, Department of Economics Spring Final Exam. Answer TWO questions. All questions carry equal weight. Time allowed 2 hours.

Mechanism Design: Bayesian Incentive Compatibility

Combinatorial Auction-Based Allocation of Virtual Machine Instances in Clouds

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012

Knapsack Auctions. Sept. 18, 2018

Lecture 4. 1 Examples of Mechanism Design Problems

Core-selecting package auctions. Han Dong, Hajir Roozbehani

A Preliminary Introduction to Mechanism Design. Theory

On Random Sampling Auctions for Digital Goods

The Revenue Equivalence Theorem 1

Vickrey Auction VCG Characterization. Mechanism Design. Algorithmic Game Theory. Alexander Skopalik Algorithmic Game Theory 2013 Mechanism Design

NTU IO (I) : Auction Theory and Mechanism Design II Groves Mechanism and AGV Mechansim. u i (x, t i, θ i ) = V i (x, θ i ) + t i,

Mechanism Design. Terence Johnson. December 7, University of Notre Dame. Terence Johnson (ND) Mechanism Design December 7, / 44

Lecture 6 Games with Incomplete Information. November 14, 2008

Simplified Mechanisms

Department of Economics, University of California, Davis Ecn 200C Micro Theory Professor Giacomo Bonanno ANSWERS TO PRACTICE PROBLEMS 18

Mechanism Design II. Terence Johnson. University of Notre Dame. Terence Johnson (ND) Mechanism Design II 1 / 30

Sequential Search Auctions with a Deadline

On Ascending Vickrey Auctions for Heterogeneous Objects

Tropical Geometry in Economics

Answer Key for M. A. Economics Entrance Examination 2017 (Main version)

Motivation. Game Theory 24. Mechanism Design. Setting. Preference relations contain no information about by how much one candidate is preferred.

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012

On the strategic use of quality scores in keyword auctions Full extraction of advertisers surplus

Sequential Bidding in the Bailey-Cavallo Mechanism

Theory of Auctions. Carlos Hurtado. Jun 23th, Department of Economics University of Illinois at Urbana-Champaign

Inefficient Equilibria of Second-Price/English Auctions with Resale

CS599: Algorithm Design in Strategic Settings Fall 2012 Lecture 1: Introduction and Class Overview. Instructor: Shaddin Dughmi

Game Theory: introduction and applications to computer networks

Revenue Guarantee Equivalence

Payment Rules for Combinatorial Auctions via Structural Support Vector Machines

Mechanism Design: Dominant Strategies

Game Theory. Monika Köppl-Turyna. Winter 2017/2018. Institute for Analytical Economics Vienna University of Economics and Business

On Ascending Vickrey Auctions for Heterogeneous Objects

Advanced Microeconomics II

Lecture Slides - Part 4

Algorithmic Game Theory and Applications

Mechanism Design: Review of Basic Concepts

Notes on Mechanism Designy

Bidding Strategy in Proxied Package Auctions with. Complementarities 1

Optimal Auctions with Correlated Bidders are Easy

DEPARTMENT OF ECONOMICS YALE UNIVERSITY P.O. Box New Haven, CT

Designing Optimal Pre-Announced Markdowns in the Presence of Rational Customers with Multi-unit Demands - Online Appendix

THEORIES ON AUCTIONS WITH PARTICIPATION COSTS. A Dissertation XIAOYONG CAO

CS 573: Algorithmic Game Theory Lecture date: April 11, 2008

NETS 412: Algorithmic Game Theory March 28 and 30, Lecture Approximation in Mechanism Design. X(v) = arg max v i (a)

EconS Advanced Microeconomics II Handout on Mechanism Design

Lecture 10: Mechanism Design

Graph Theoretic Characterization of Revenue Equivalence

Ph.D. Preliminary Examination MICROECONOMIC THEORY Applied Economics Graduate Program May 2012

Information Acquisition in Interdependent Value Auctions

Mechanism Design for Multiagent Systems

Module 18: VCG Mechanism

Mechanism Design with Approximate Valuations. Alessandro Chiesa Silvio Micali Zeyuan Allen Zhu

COOPERATIVE GAME THEORY: CORE AND SHAPLEY VALUE

Introduction to Mechanism Design

The Sample Complexity of Revenue Maximization in the Hierarchy of Deterministic Combinatorial Auctions

Welfare Maximization in Combinatorial Auctions

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Thursday 17th May 2018 Time: 09:45-11:45. Please answer all Questions.

Parking Space Assignment Problem: A Matching Mechanism Design Approach

Mechanism Design without Quasilinearity

Gerard van der Laan, Dolf Talman, and Zaifu Yang

A Dynamic Market Clearing Price Mechanism with Multiple Demands *

Vasilis Syrgkanis Microsoft Research NYC

Revenue Monotonicity in Combinatorial Auctions

Mechanisms with Unique Learnable Equilibria

Second Price Auctions with Differentiated Participation Costs

An Efficient and Incentive Compatible Ascending Auction for Multiple Complements 1

Sealed-bid first-price auctions with an unknown number of bidders

Microeconomics II Lecture 4: Incomplete Information Karl Wärneryd Stockholm School of Economics November 2016

Economics 2102: Final Solutions

Some Lecture Notes on Auctions

Monopoly with Resale. Supplementary Material

Lecture 6: Communication Complexity of Auctions

Query and Computational Complexity of Combinatorial Auctions

Stability and Incentive Compatibility in a Kernel-Based Combinatorial Auction

Characterization of the Walrasian equilibria of the assignment model Mishra, D.; Talman, Dolf

Bayesian Games and Auctions

Robustly Optimal Auctions with Unknown Resale Opportunities. [Formatted manuscript; volume and page numbers to be changed later]

CS 598RM: Algorithmic Game Theory, Spring Practice Exam Solutions

A Structural Model of Sponsored Search Advertising Auctions

Microeconomic Theory (501b) Problem Set 10. Auctions and Moral Hazard Suggested Solution: Tibor Heumann

Perfect Bayesian Equilibrium. Definition. The single-crossing property. This is a draft; me with comments, typos, clarifications, etc.

The Competition Complexity of Auctions: Bulow-Klemperer Results for Multidimensional Bidders

CS364B: Frontiers in Mechanism Design Lecture #2: Unit-Demand Bidders and Walrasian Equilibria

Preliminary notes on auction design

Mediators in Position Auctions

Redistribution Mechanisms for Assignment of Heterogeneous Objects

Multiple-Object Auctions with Budget Constrained Bidders

Revenue Maximization in Multi-Object Auctions

Mechanism Design: Bargaining

Online Appendix for "Auctions in Markets: Common Outside Options and the Continuation Value Effect" Not intended for publication

Online Appendix for Dynamic Ex Post Equilibrium, Welfare, and Optimal Trading Frequency in Double Auctions

Algorithmic Game Theory Introduction to Mechanism Design

Transcription:

A Review of Auction Theory: and Vickrey Daniel R. 1 1 Department of Economics University of Maryland, College Park. September 2017 / Econ415

. Vickrey s. Vickrey.

Example Two goods, one per bidder Suppose we have the standard IPV situation with n >2 bidders and the seller has 2 objects to sell and each bidder desires a single object. The seller could modify the to a Third Price Auction (highest losing bid for two objects) and all our previous results concerning dominant strategies would carry over. Alternatively, she could conduct two in sequence, each selling a single object. How would a bidder bid in the second of the two auctions? What would be the expected price? Knowing this, how would bidders bid in the first of the two auctions? Although the actual equilibrium prices might differ from the TPA, in expectation, the prices will be the same.. Why?

Example Two goods, many per bidder Suppose we have n = 3 bidders and the seller has 2 objects to sell. Two bidders desire a single object A for 100 and B for 50 or 100. The remaining bidder only wants both objects AB for 180. (Example, telecom footprint.) Suppose with two s, A is sold then B. Suppose large bidder buys A for x(= 100) > 0. What should it bid for B? If the remaining single object bidder bids 50, then large bidder is ok. But what if it bids $100? Large bidder is exposed and risks losing a lot at the auction. Problem arises because for small bidders, objects are substitutes, while for large bidder, they are complements.

General Setup Suppose that there are M objects and n bidders have positive value for any subset of them. Show that there are 2 M possible subsets. For any subset C, the bidder s willingness to pay is v C. What are conditions on {v C } that create exposure issues? C, D, C D =, v C D > v C + v D. How to sell all subsets to many potential buyers? Let D be the set of all possible allocations of subsets to n bidders. Computing D is a complicated fitting problem.

Set-up allocation The type θ j of a bidder is the collection of values v j C the bidder places on each possible subset C it could acquire. If the bidder acquires C j and pays t j it gets v j C j t j. Bidders report to the auction, a claim of θ j (it does not have to be the truth). For any report, θ = (θ 1, θ 2,..., θ n ), the auctioneer computes W (θ) = max (C1,...,C n) D and selects this allocation, C(θ). n j=1 v j C j

Set-up payment For any report, θ, and bidder i the auctioneer computes W i (θ i ) = max C D Bidder i must pay the difference n v j C j j i t i (θ) = W i (θ i ) j i v j C j (θ). Observe that if the report of bidder i does not change the allocation to the other bidders, bidder i pays zero. Otherwise, bidder i is termed a pivotal bidder.

Main Result It is a weakly dominant strategy to report your true values to the mechanism. As long as bidders follow their dominant strategy, the mechanism is efficient it maximizes total bidder value. With just one object, the mechanism collapses to a. Show. Compute the equilibrium outcome for the exposure example. Compute.

Example 1 3 objects and 3 bidders. Note that in general, each bidder will have 8 = 2 3 values to report. They are reported in the following table. B 1 B 2 B 3 0 0 0 a 1 2 3 b 1 1 3 c 1 2 2 ab 2 3 3 ac 2 4 3 bc 3 3 3 abc 5 5 5

Example 2: Low Revenues (From Ausubel/Milgrom) 2 objects and 3 bidders. The values (in Billions of dollars) are reported in the following table. B 1 B 2 B 3 0 0 0 a 2 2 0 b 2 2 0 ab 2 2 2 Suppose the licenses were sold as a bundle only. Revenue and efficiency. What would occur with only bidder B1 and B3? Compare it to having all three bidders.

Criticisms Complexity. Size of bid space rises rapidly. Lack of price discovery. Related to complexity. Also, need to learn about market. Failure of monotonicity in number of bidders. Examples Vulnerability to collusive behavior. Examples. Potential for very low revenues. Examples.