Approximation in mechanism design with interdependent values
Yunan Li
Games and Economic Behavior, 2017, vol. 103, issue C, 225-253
Abstract:
This paper studies the revenue maximization problem in environments wherein buyers have interdependent values and correlated types. We show that (1) when the system of feasible sets is a matroid and buyer valuations satisfy a single-crossing condition, the generalized Vickrey–Clarke–Groves mechanisms with lazy reserves (VCG-L) are ex-post incentive compatible and ex-post individually rational; (2) if, in addition, the valuation distribution satisfies a generalized monotone hazard rate condition, the VCG-L mechanism with conditional monopoly reserves is approximately optimal. Then we construct an ascending auction that implements the truth-telling equilibrium of a VCG-L mechanism in ex-post equilibrium. Finally, we discuss the connection between the VCG-L mechanisms and greedy algorithms studied in Lehmann et al. (2002) and deferred-acceptance auctions studied in Milgrom and Segal (2014), and the impact of competition by proving a Bulow and Klemperer (1996) type result.
Keywords: Mechanism design; Approximation; Interdependent values; Revenue maximization (search for similar items in EconPapers)
JEL-codes: D44 D82 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0899825616000099
Full text for ScienceDirect subscribers only
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:eee:gamebe:v:103:y:2017:i:c:p:225-253
DOI: 10.1016/j.geb.2016.01.006
Access Statistics for this article
Games and Economic Behavior is currently edited by E. Kalai
More articles in Games and Economic Behavior from Elsevier
Bibliographic data for series maintained by Catherine Liu ().