Ranking opportunity sets: An approach based on the preference for flexibility
Ricardo Arlegi () and
Jorge Nieto ()
Additional contact information
Ricardo Arlegi: Departamento de EconomÎa, Universidad Pßblica de Navarra, Campus de ArrosadÎa, 31006 Pamplona, Spain
Jorge Nieto: Departamento de EconomÎa, Universidad Pßblica de Navarra, Campus de ArrosadÎa, 31006 Pamplona, Spain
Social Choice and Welfare, 2001, vol. 18, issue 1, 23-36
Abstract:
We describe a criterion to evaluate subsets of a finite set of alternatives which are considered as opportunity sets. The axioms for set comparison are motivated within the preference for flexibility framework. We assume the preference over the universal set of alternatives to be made of two disjoint binary relations. The result is the axiomatic characterization of a procedure which is formally similar to the leximax ordering, but in our case it incorporates the presence of some uncertainty about the decision-maker final tastes.
Date: 2001-01-10
Note: Received: 20 January 1999/Accepted: 20 October 1999
References: Add references at CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
http://link.springer.de/link/service/journals/00355/papers/1018001/10180023.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:sochwe:v:18:y:2001:i:1:p:23-36
Ordering information: This journal article can be ordered from
http://www.springer. ... c+theory/journal/355
Access Statistics for this article
Social Choice and Welfare is currently edited by Bhaskar Dutta, Marc Fleurbaey, Elizabeth Maggie Penn and Clemens Puppe
More articles in Social Choice and Welfare from Springer, The Society for Social Choice and Welfare Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().