Optimal allocation without transfer payments

Surajeet Chakravarty and Todd Kaplan

Games and Economic Behavior, 2013, vol. 77, issue 1, 1-20

Abstract: Often an organization or government must allocate goods without collecting payment in return. This may pose a difficult problem either when agents receiving those goods have private information in regards to their values or needs. In this paper, we find an optimal mechanism to allocate goods when the designer is benevolent. While the designer cannot charge agents, he can receive a costly but wasteful signal from them. We find conditions for cases in which ignoring these costly signals by giving agents equal share (or using lotteries if the goods are indivisible) is optimal. In other cases, those that send the highest signal should receive the goods; however, we then show that there exist cases where more complicated mechanisms are superior. Also, we show that the optimal mechanism is independent of the scarcity of the goods being allocated.

Keywords: Mechanism design; Allocation (search for similar items in EconPapers)
JEL-codes: C70 D44 D89 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0899825612001261
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Optimal Allocation without Transfer Payments (2010)
Working Paper: Optimal Allocation without Transfer Payments (2009)
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:77:y:2013:i:1:p:1-20

DOI: 10.1016/j.geb.2012.08.006

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 ().