Bayesian optimal no-deficit mechanism design

Shuchi Chawla*, Jason D. Hartline, Uday Rajan, R. Ravi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


One of the most fundamental problems in mechanism design is that of designing the auction that gives the optimal profit to the auctioneer. For the case that the probability distributions on the valuations of the bidders are known and independent, Myerson [15] reduces the problem to that of maximizing the common welfare by considering the virtual valuations in place of the bidders' actual valuations. The Myerson auction maximizes the seller's profit over the class of all mechanisms that are truthful and individually rational for all the bidders; however, the mechanism does not satisfy ex post individual rationality for the seller. In other words, there are examples in which for certain sets of bidder valuations, the mechanism incurs a loss. We consider the problem of merging the worst case no-deficit (or ex post seller individual rationality) condition with this average case Bayesian expected profit maximization problem. When restricting our attention to ex post incentive compatible mechanisms for this problem, we find that the Myerson mechanism is the optimal no-deficit mechanism for supermodular costs, that Myerson merged with a simple thresholding mechanism is optimal for all-or-nothing costs, and that neither mechanism is optimal for general submodular costs. Addressing the computational side of the problem, we note that for supermodular costs the Myerson mechanism is NP-hard to compute. Furthermore, we show that for all-or-nothing costs the optimal thresholding mechanism is NP-hard to compute. Finally, we consider relaxing the ex post incentive compatibility constraint and show that there is a Bayesian incentive compatible mechanism that achieves the same expected profit as Myerson, but never incurs a loss.

Original languageEnglish (US)
Title of host publicationInternet and Network Economics - Second International Workshop, WINE 2006, Proceedings
Number of pages13
StatePublished - 2006
Event2nd International Workshop on Internet and Network Economics, WINE 2006 - Patras, Greece
Duration: Dec 15 2006Dec 17 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4286 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2nd International Workshop on Internet and Network Economics, WINE 2006

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Bayesian optimal no-deficit mechanism design'. Together they form a unique fingerprint.

Cite this