Aggregable Health Inequality Indices
Stéphane Mussard,
Maria Pi Alperin and
Véronique Thireau
No 2016-11, LISER Working Paper Series from Luxembourg Institute of Socio-Economic Research (LISER)
Abstract:
An aggregable family of multidimensional concentration indices is characterized, in order to be consistent with a property of exogenous risk factors, i.e. health risks for which agents are not responsible for. The family of concentration indices (or achievement indices by duality) lies in the class of polynomial functions. Necessary and suffcient conditions are stated in order to rank two health distributions thanks to the generalized concentration curves. It is shown that the properties of mirror and symmetry are compatible with a sub-family of concentration indices being polynomial functions. A dominance criterion exists for this sub-family of indices, provided that the decision maker is an inequality lover.
Keywords: Concentration; Dominance; Health inequality; Mirror; Symmetry (search for similar items in EconPapers)
JEL-codes: D60 I10 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2016-07
New Economics Papers: this item is included in nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.liser.lu/publi_viewer.cfm?tmp=3985 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found
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:irs:cepswp:2016-11
Access Statistics for this paper
More papers in LISER Working Paper Series from Luxembourg Institute of Socio-Economic Research (LISER) 11, Porte des Sciences, L-4366 Esch-sur-Alzette, G.-D. Luxembourg. Contact information at EDIRC.
Bibliographic data for series maintained by Library and Documentation ( this e-mail address is bad, please contact ).