Ordinal efficiency under the lens of duality theory
Stergios Athanassoglou
Authors registered in the RePEc Author Service: Stergios Athanasoglou
MPRA Paper from University Library of Munich, Germany
Abstract:
An allocation's ordinal efficiency deficit (OED) is defined as the greatest ordinal efficiency loss that can result from its application. More precisely, an allocation's OED is the negative of the greatest total amount by which it may be stochastically dominated by another feasible allocation. Thus, an allocation is ordinally efficient if and only if its OED is zero. Using this insight, we set up a linear program whose optimal objective value corresponds to a given allocation's OED. Furthermore, we show that the OED is a piecewise-linear convex function on the set of allocations. We use the optimal dual variables of the linear program to construct a profile of von Neumann-Morgenstern (vNM) utilities that is compatible with the underlying ordinal preferences, and which is a subgradient of the OED at the given allocation. When the given allocation is ordinally efficient, our analysis implies that it is ex-ante welfare maximizing at the constructed vNM profile, and we recover the ordinal efficiency theorem due to McLennan (2002)
Keywords: random assignment; ordinal efficiency; linear programming; duality (search for similar items in EconPapers)
JEL-codes: C61 D01 D60 (search for similar items in EconPapers)
Date: 2010-08-20
New Economics Papers: this item is included in nep-gth and nep-mic
References: Add references at CitEc
Citations:
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/26331/1/MPRA_paper_26331.pdf original version (application/pdf)
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:pra:mprapa:26331
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().