Optimal and Efficient Parametric Auctions
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Author(s)
Azar, Pablo Daniel
Micali, Silvio
Weinberg, S. Matthew
Daskalakis, Konstantinos
Date Issued
2013
Journal
Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA '13
Publisher
Society for Industrial and Applied Mathematics
Citation
Azar, Pablo, Silvio Micali, Constantinos Daskalakis, and S. Matthew Weinberg. “Optimal and Efficient Parametric Auctions.” Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms (January 6, 2013): 596–604. © SIAM
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Final published version
Abstract
Consider a seller who seeks to provide service to a collection of interested parties, subject to feasibility constraints on which parties may be simultaneously served. Assuming that a distribution is known on the value of each party for service—arguably a strong assumption—Myerson's seminal work provides revenue optimizing auctions [12]. We show instead that, for very general feasibility constraints, only knowledge of the median of each party's value distribution, or any other quantile of these distributions, or approximations thereof, suffice for designing simple auctions that simultaneously approximate both the optimal revenue and the optimal welfare. Our results apply to all downward-closed feasibility constraints under the assumption that the underlying, unknown value distributions are monotone hazard rate, and to all matroid feasibility constraints under the weaker assumption of regularity of the underlying distributions. Our results jointly generalize the single-item results obtained by Azar and Micali [2] on parametric auctions, and Daskalakis and Pierrakos [6] for simultaneously approximately optimal and efficient auctions.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1137/1.9781611973105.43
