research-article

Approximate revenue maximization in interdependent value settings

Authors:

Anna KarlinAuthors Info & Claims

EC '14: Proceedings of the fifteenth ACM conference on Economics and computation

Pages 277 - 294

https://doi.org/10.1145/2600057.2602858

Published: 01 June 2014 Publication History

Abstract

We study revenue maximization in settings where agents' values are interdependent: each agent receives a signal drawn from a correlated distribution and agents' values are functions of all of the signals. We introduce a variant of the generalized VCG auction with reserve prices and random admission, and show that this auction gives a constant approximation to the optimal expected revenue in matroid environments. Our results do not require any assumptions on the signal distributions, however, they require the value functions to satisfy a standard single-crossing property and a concavity-type condition.

References

[1]

Abraham, I., Athey, S., Babaioff, M., and Grubb, M. 2013. Peaches, lemons, and cookies: designing auction markets with dispersed information. In ACM Conference on Electronic Commerce.

Digital Library

[2]

Ausubel, L. 1999. A generalized vickrey auction. Econometrica.

[3]

Azar, P., Daskalakis, C., Micali, S., and Weinberg, S. M. 2013. Optimal and efficient parametric auctions. In 24th ACM-SIAM Symposium on Discrete Algorithms.

Digital Library

[4]

Babaioff, M., Kleinberg, R., and Leme, R. P. 2012. Optimal mechanisms for selling information. In ACM Conference on Electronic Commerce.

Digital Library

[5]

Chung, K. and Ely, J. 2006. Ex-post incentive compatible mechanism design. Unpublished manuscript.

[6]

Chung, K.-S. and Ely, J. C. 2007. Foundations of dominant-strategy mechanisms. The Review of Economic Studies 74, 2, 447--476.

[7]

Clarke, E. H. 1971. Multipart pricing of public goods. Public Choice 2, 19--33.

[8]

Crémer, J. and McLean, R. 1985. Optimal selling strategies under uncertainty for a discriminating monopolist when demands are interdependent. Econometrica 53, 2.

[9]

Crémer, J. and McLean, R. 1988. Full extraction of the surplus in bayesian and dominant strategy auctions. Econometrica 56, 6.

[10]

Dasgupta, P. and Maskin, E. 2000. Efficient auctions. The Quarterly Journal of Economics 115, 2, 341--388.

[11]

Devanur, N., Hartline, J., Karlin, A., and Nguyen, T. 2011. Prior-independent multi-parameter mechanism design. In Internet and Network Economics. Springer, 122--133.

Digital Library

[12]

Dhangwatnotai, P., Roughgarden, T., and Yan, Q. 2010. Revenue maximization with a single sample. In ACM Conference on Electronic Commerce. 129--138.

Digital Library

[13]

Dobzinski, S., Fu, H., and Kleinberg, R. D. 2011. Optimal auctions with correlated bidders are easy. In STOC. 129--138.

Digital Library

[14]

Groves, T. 1973. Incentives in Teams. Econometrica 41, 617--631.

[15]

Hartline, J. D. and Roughgarden, T. 2009. Simple versus optimal mechanisms. In ACM Conference on Electronic Commerce. 225--234.

Digital Library

[16]

Klemperer, P. 1998. Auctions with almost common values: The 'wallet game' and its applications. European Economic Review 42, 3--5, 757--769.

[17]

Krishna, V. 2010. Auction Theory. Academic Press.

[18]

Li, Y. 2013. Approximation in mechanism design with interdependent values. In ACM Conference on Electronic Commerce. 675--676.

Digital Library

[19]

Lopomo, G. 2000. Optimality and robustness of the english auction. Games and Economic Behavior 36, 219--240.

[20]

McAfee, R. P., McMillan, J., and Reny, P. J. 1989. Extracting the surplus in the common-value auction. Econometrica, 1451--1459.

[21]

McAfee, R. P. and Reny, P. J. 1992. Correlated information and mechanism design. Econometrica 60, 2, 395--421.

[22]

Milgrom, P. 2004. Putting Auction Theory to Work. Cambridge University Press.

[23]

Milgrom, P. and Weber, R. J. 1982. A theory of auctions and competitive bidding. Econometrica 50, 1089--1122.

[24]

Myerson, R. 1981. Optimal auction design. Mathematics of Operations Research 6, 1, pp. 58--73.

Digital Library

[25]

Neeman, Z. 2003. The effectiveness of english auctions. Games and Economic Behavior 43, 2, 214--238.

[26]

Papadimitiou, C. and Pierrakos, G. 2011. On optimal single-item auctions. In STOC. 119--128.

Digital Library

[27]

Rahman, D. 2014. Surplus extraction on arbitrary type spaces. Forthcoming in Theoretical Economics.

[28]

Ronen, A. 2001. On approximating optimal auctions. In ACM Conference on Electronic Commerce. 11--17.

Digital Library

[29]

Roughgarden, T. and Talgam-Cohen, I. 2013. Optimal and near-optimal mechanism design with interdependent values. In ACM Conference on Electronic Commerce. 767--784.

Digital Library

[30]

Roughgarden, T., Talgam-Cohen, I., and Yan, Q. 2012. Supply-limiting mechanisms. In ACM Conference on Electronic Commerce. 844--861.

Digital Library

[31]

Schrijver, A. 2003. Combinatorial Optimization : Polyhedra and Efficiency (Algorithms and Combinatorics). Springer.

[32]

Segal, I. 2003. Optimal pricing mechanisms with unknown demand. American Economic Review 93.

[33]

Syrgkanis, V., Kempe, D., and Tardos, E. 2013. Information asymmetries in common-value auctions with discrete signals. In SSRN.

[34]

Vickrey, W. 1961. Counterspeculation, Auctions and Competitive Sealed Tenders. Journal of Finance, 8--37.

[35]

Vohra, R. 2011. Mechanism Design: A Linear Programming Approach. Cambridge University Press.

[36]

Wilson, R. 1969. Competitive bidding with disparate information. Management Sciences 15.

Cited By

Eden AFeldman MMauras SMohan DKleinberg RSaban DBergemann D(2024)Private Interdependent Valuations: New Bounds for Single-Item Auctions and MatroidsProceedings of the 25th ACM Conference on Economics and Computation10.1145/3670865.3673581(448-464)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3670865.3673581
Abada ASt-Hilaire MWei Shi a(2024)Balancing Power Grids and Maximizing Revenue: A Novel Approach to Rebate Auctions for Cloud Workload MigrationsIEEE Access10.1109/ACCESS.2024.349301212(172969-172979)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3493012
Chen MLiu YShen WShen YTang PYang Q(2024)A Mechanism Design Approach for Multi-Party Machine LearningTheoretical Computer Science10.1016/j.tcs.2024.114618(114618)Online publication date: May-2024
https://doi.org/10.1016/j.tcs.2024.114618
Show More Cited By

Index Terms

Approximate revenue maximization in interdependent value settings
1. Applied computing
  1. Law, social and behavioral sciences
    1. Economics

Recommendations

Optimal and Robust Mechanism Design with Interdependent Values
Special Issue on EC'13

We study interdependent value settings and extend several results from the well-studied independent private values model to these settings. For revenue-optimal mechanism design, we give conditions under which Myerson's virtual value-based mechanism ...
Simple Mechanisms for a Subadditive Buyer and Applications to Revenue Monotonicity
Special Issue on EC'15

We study the revenue maximization problem of a seller with n heterogeneous items for sale to a single buyer whose valuation function for sets of items is unknown and drawn from some distribution D. We show that if D is a distribution over subadditive ...
Differentially private spectrum auction with approximate revenue maximization
MobiHoc '14: Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing

Dynamic spectrum redistribution---under which spectrum owners lease out under-utilized spectrum to users for financial gain---is an effective way to improve spectrum utilization. Auction is a natural way to incentivize spectrum owners to share their idle ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

EC '14: Proceedings of the fifteenth ACM conference on Economics and computation

June 2014

1028 pages

ISBN:9781450325653

DOI:10.1145/2600057

General Chair:
Moshe Babaioff
Microsoft Research
,
Program Chairs:
Vincent Conitzer
Duke University
,
David Easley
Cornell University

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGecom: Special Interest Group on Economics and Computation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Division of Computing and Communication Foundations

Conference

EC '14

Sponsor:

SIGecom

EC '14: ACM Conference on Economics and Computation

June 8 - 12, 2014

California, Palo Alto, USA

Acceptance Rates

EC '14 Paper Acceptance Rate 80 of 290 submissions, 28%;

Overall Acceptance Rate 664 of 2,389 submissions, 28%

Upcoming Conference

EC '25

Sponsor:
sigecom

The 25th ACM Conference on Economics and Computation

July 7 - 11, 2025

Stanford , CA , USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

19
Total Citations
View Citations
208
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)1

Reflects downloads up to 13 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Eden AFeldman MMauras SMohan DKleinberg RSaban DBergemann D(2024)Private Interdependent Valuations: New Bounds for Single-Item Auctions and MatroidsProceedings of the 25th ACM Conference on Economics and Computation10.1145/3670865.3673581(448-464)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3670865.3673581
Abada ASt-Hilaire MWei Shi a(2024)Balancing Power Grids and Maximizing Revenue: A Novel Approach to Rebate Auctions for Cloud Workload MigrationsIEEE Access10.1109/ACCESS.2024.349301212(172969-172979)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3493012
Chen MLiu YShen WShen YTang PYang Q(2024)A Mechanism Design Approach for Multi-Party Machine LearningTheoretical Computer Science10.1016/j.tcs.2024.114618(114618)Online publication date: May-2024
https://doi.org/10.1016/j.tcs.2024.114618
Shen WTang PZuo SShen WTang PZuo S(2024)Multi-objective Mechanism Design via AI-Driven ApproachesAI-Driven Mechanism Design10.1007/978-981-97-9286-3_4(95-127)Online publication date: 30-Sep-2024
https://doi.org/10.1007/978-981-97-9286-3_4
Eden AFeldman MGoldner KMauras SMohan D(2023)Constant Approximation for Private Interdependent Valuations2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS)10.1109/FOCS57990.2023.00018(148-163)Online publication date: 6-Nov-2023
https://doi.org/10.1109/FOCS57990.2023.00018
Chen MLiu YShen WShen YTang PYang Q(2023)A Mechanism Design Approach for Multi-party Machine LearningFrontiers of Algorithmic Wisdom10.1007/978-3-031-20796-9_18(248-268)Online publication date: 1-Jan-2023
https://doi.org/10.1007/978-3-031-20796-9_18
Lu PSun EZhou C(2022)Better Approximation for Interdependent SOS ValuationsWeb and Internet Economics10.1007/978-3-031-22832-2_13(219-234)Online publication date: 9-Dec-2022
https://doi.org/10.1007/978-3-031-22832-2_13
Feng YHartline JLi YKhuller SVassilevska Williams V(2021)Revelation gap for pricing from samplesProceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing10.1145/3406325.3451057(1438-1451)Online publication date: 15-Jun-2021
https://dl.acm.org/doi/10.1145/3406325.3451057
Gkatzelis VPatel RPountourakis ESchoepflin D(2021)Prior-Free Clock Auctions for Bidders with Interdependent ValuesAlgorithmic Game Theory10.1007/978-3-030-85947-3_5(64-78)Online publication date: 14-Sep-2021
https://doi.org/10.1007/978-3-030-85947-3_5
Amer ATalgam-Cohen I(2021)Auctions with Interdependence and SOS: Improved ApproximationAlgorithmic Game Theory10.1007/978-3-030-85947-3_3(34-48)Online publication date: 14-Sep-2021
https://doi.org/10.1007/978-3-030-85947-3_3
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents