Strategy-proofness versus efficiency for small domains of preferences over public goods

James Schummer

Economic Theory, 1999, vol. 13, issue 3, 709-722

Abstract: It has long been known that when agents have von Neumann-Morgenstern preferences over lotteries, there is an incompatibility between strategy-proofness and efficiency (Gibbard, [9]; Hylland, [12]) - a solution satisfying those properties must be dictatorial. We strengthen this result by showing that it follows from the same incompatibility on a series of much smaller domains of preferences. Specifically, we first show the incompatibility to hold on our smallest domain, in which two agents are restricted to have linear preferences over one private good and one public good produced from the private good (Kolm triangle economies). This result then implies the same incompatibility on increasingly larger domains of preferences, ending finally with the class of von Neumann-Morgenstern preferences over lotteries.

Keywords: Strategyproof; Public; goods; ·; Lotteries.; · (search for similar items in EconPapers)
Date: 1999-04-15
Note: Received: February 6, 1997; revised version: January 29, 1998
References: Add references at CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://link.springer.de/link/service/journals/00199/papers/9013003/90130709.pdf (application/pdf)
Access to the full text of the articles in this series is restricted

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:spr:joecth:v:13:y:1999:i:3:p:709-722

Ordering information: This journal article can be ordered from
http://www.springer. ... eory/journal/199/PS2

Access Statistics for this article

Economic Theory is currently edited by Nichoals Yanneils

More articles in Economic Theory from Springer, Society for the Advancement of Economic Theory (SAET) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().