Algorithmic Game Theory
Bayesian Combinatorial Auctions
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
On Maximizing Welfare When Utility Functions Are Subadditive
SIAM Journal on Computing
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Price of anarchy for greedy auctions
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
GSP auctions with correlated types
Proceedings of the 12th ACM conference on Electronic commerce
On the efficiency of equilibria in generalized second price auctions
Proceedings of the 12th ACM conference on Electronic commerce
Non-price equilibria in markets of discrete goods
Proceedings of the 12th ACM conference on Electronic commerce
Welfare guarantees for combinatorial auctions with item bidding
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Proceedings of the 13th ACM Conference on Electronic Commerce
The price of anarchy in games of incomplete information
Proceedings of the 13th ACM Conference on Electronic Commerce
Uniform price auctions: equilibria and efficiency
SAGT'12 Proceedings of the 5th international conference on Algorithmic Game Theory
Simultaneous single-item auctions
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Setting equilibrium prices, approximately
ACM SIGecom Exchanges
Price competition in online combinatorial markets
Proceedings of the 23rd international conference on World wide web
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Simultaneous item auctions are simple and practical procedures for allocating items to bidders with potentially complex preferences. In a simultaneous auction, every bidder submits independent bids on all items simultaneously. The allocation and prices are then resolved for each item separately, based solely on the bids submitted on that item. We study the efficiency of Bayes-Nash equilibrium (BNE) outcomes of simultaneous first- and second-price auctions when bidders have complement-free (a.k.a. subadditive) valuations. While it is known that the social welfare of every pure Nash equilibrium (NE) constitutes a constant fraction of the optimal social welfare, a pure NE rarely exists, and moreover, the full information assumption is often unrealistic. Therefore, quantifying the welfare loss in Bayes-Nash equilibria is of particular interest. Previous work established a logarithmic bound on the ratio between the social welfare of a BNE and the expected optimal social welfare in both first-price auctions (Hassidim et al., 2011) and second-price auctions (Bhawalkar and Roughgarden, 2011), leaving a large gap between a constant and a logarithmic ratio. We introduce a new proof technique and use it to resolve both of these gaps in a unified way. Specifically, we show that the expected social welfare of any BNE is at least 1/2 of the optimal social welfare in the case of first-price auctions, and at least 1/4 in the case of second-price auctions.