Limits of efficiency in sequential auctions

Michal Feldman, Brendan Lucier, Vasilis Syrgkanis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We study the efficiency of sequential first-price item auctions at (subgame perfect) equilibrium. This auction format has recently attracted much attention, with previous work establishing positive results for unit-demand valuations and negative results for submodular valuations. This leaves a large gap in our understanding between these valuation classes. In this work we resolve this gap on the negative side. In particular, we show that even in the very restricted case in which each bidder has either an additive valuation or a unit-demand valuation, there exist instances in which the inefficiency at equilibrium grows linearly with the minimum of the number of items and the number of bidders. Moreover, these inefficient equilibria persist even under iterated elimination of weakly dominated strategies. Our main result implies linear inefficiency for many natural settings, including auctions with gross substitute valuations, capacitated valuations, budget-additive valuations, and additive valuations with hard budget constraints on the payments. For capacitated valuations, our results imply a lower bound that equals the maximum capacity of any bidder, which is tight following the upper-bound technique established by Paes Leme et al. [20].

Original languageEnglish
Title of host publicationWeb and Internet Economics - 9th International Conference, WINE 2013, Proceedings
Number of pages14
StatePublished - 2013
Externally publishedYes
Event9th International Conference on Web and Internet Economics, WINE 2013 - Cambridge, MA, United States
Duration: 11 Dec 201314 Dec 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8289 LNCS


Conference9th International Conference on Web and Internet Economics, WINE 2013
Country/TerritoryUnited States
CityCambridge, MA

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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