Capturing preferences for inequality aversion in decision support
Karsu, Özlem and Morton, Alec and Argyris, Nikos (2018) Capturing preferences for inequality aversion in decision support. European Journal of Operational Research, 264 (2). pp. 686-706. ISSN 0377-2217 (https://doi.org/10.1016/j.ejor.2017.07.018)
Preview |
Text.
Filename: Karsu_etal_EJOR_2017_Capturing_preferences_for_inequality_aversion_in_decision.pdf
Accepted Author Manuscript License: Download (544kB)| Preview |
Abstract
We investigate the situation where there is interest in ranking distributions (of income, of wealth, of health, of service levels) across a population, in which individuals are considered preferentially indistinguishable and where there is some limited information about social pref- erences. We use a natural dominance relation, generalized Lorenz dominance, used in welfare comparisons in economic theory. In some settings there may be additional information about preferences (for example, if there is policy statement that one distribution is preferred to an- other) and any dominance relation should respect such preferences. However, characterising this sort of conditional dominance relation (specifically, dominance with respect to the set of all symmetric increasing quasiconcave functions in line with given preference information) turns out to be computationally challenging. This challenge comes about because, through the as- sumption of symmetry, any one preference statement (“I prefer giving $100 to Jane and $110 to John over giving $150 to Jane and $90 to John”) implies a large number of other preference statements (“I prefer giving $110 to Jane and $100 to John over giving $150 to Jane and $90 to John”; “I prefer giving $100 to Jane and $110 to John over giving $90 to Jane and $150 to John”). We present theoretical results that help deal with these challenges and present tractable linear programming formulations for testing whether dominance holds between any given pair of distributions. We also propose an interactive decision support procedure for ranking a given set of distributions and demonstrate its performance through computational testing.
ORCID iDs
Karsu, Özlem, Morton, Alec ORCID: https://orcid.org/0000-0003-3803-8517 and Argyris, Nikos;-
-
Item type: Article ID code: 61196 Dates: DateEvent16 January 2018Published10 July 2017Published Online1 July 2017AcceptedSubjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management Department: Strathclyde Business School > Management Science
Strategic Research Themes > Health and WellbeingDepositing user: Pure Administrator Date deposited: 03 Jul 2017 13:35 Last modified: 25 Nov 2024 01:13 URI: https://strathprints.strath.ac.uk/id/eprint/61196