Non-optimal Mechanism Design

Jason D. Hartline and Brendan Lucier

American Economic Review, 2015, vol. 105, issue 10, 3102-24

Abstract: The optimal allocation of resources in complex environments—like allocation of dynamic wireless spectrum, cloud computing services, and Internet advertising—is computationally challenging even given the true preferences of the participants. In the theory and practice of optimization in complex environments, a wide variety of special and general purpose algorithms have been developed; these algorithms produce outcomes that are satisfactory but not generally optimal or incentive compatible. This paper develops a very simple approach for converting any, potentially non-optimal, algorithm for optimization given the true participant preferences, into a Bayesian incentive compatible mechanism that weakly improves social welfare and revenue. (JEL D82, H82, L82)

JEL-codes: D82 H82 L82 (search for similar items in EconPapers)
Date: 2015
Note: DOI: 10.1257/aer.20130712
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.aeaweb.org/articles.php?doi=10.1257/aer.20130712 (application/pdf)
http://www.aeaweb.org/aer/app/10510/20131702_app.pdf (application/pdf)
http://www.aeaweb.org/aer/ds/10510/20131702_ds.zip (application/zip)
Access to full text is restricted to AEA members and institutional subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aea:aecrev:v:105:y:2015:i:10:p:3102-24

Ordering information: This journal article can be ordered from
https://www.aeaweb.org/journals/subscriptions

Access Statistics for this article

American Economic Review is currently edited by Esther Duflo

More articles in American Economic Review from American Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Michael P. Albert ().