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dc.contributor.authorTofallis, C.
dc.date.accessioned2013-09-04T14:15:08Z
dc.date.available2013-09-04T14:15:08Z
dc.date.issued2013
dc.identifier.citationTofallis , C 2013 , ' An automatic-democratic approach to weight setting for the new human development index. ' , Journal of Population Economics , vol. 26 , no. 4 , pp. 1325-1345 . https://doi.org/10.1007/s00148-012-0432-x
dc.identifier.issn1432-1475
dc.identifier.otherPURE: 938993
dc.identifier.otherPURE UUID: 5dfc9cd9-16eb-4a05-9de8-de4cd1e3105b
dc.identifier.otherScopus: 84884989629
dc.identifier.otherORCID: /0000-0001-6150-0218/work/34655896
dc.identifier.urihttp://hdl.handle.net/2299/11531
dc.description.abstractPerhaps the most difficult aspect of constructing a multi-dimensional index is that of choosing weights for the components. This problem is often bypassed by adopting the ‘agnostic’ option of equal weights, as in the Human Development Index. This is an annual ranking of countries produced by the United Nations Development Programme based on life expectancy, education, and per capita gross national income. These three dimensions are now aggregated multiplicatively. Whatever weights (exponents) are chosen for these dimensions, some nations will feel disadvantaged. To avoid the use of arbitrary weights we propose for consideration a two-step approach: (1) Find the most advantageous set of weights for each nation in turn. (2) Regress the associated optimal scores on the underlying indicators to find a single weight set. This approach has the properties of non-subjectivity, fairness, and convenience. The result is that the highest weight is placed on the life expectancy dimension.en
dc.format.extent21
dc.language.isoeng
dc.relation.ispartofJournal of Population Economics
dc.subjectmultidimensional
dc.subjectranking methods
dc.subjectmulticriteria analysis
dc.titleAn automatic-democratic approach to weight setting for the new human development index.en
dc.contributor.institutionDepartment of Marketing and Enterprise
dc.contributor.institutionSocial Sciences, Arts & Humanities Research Institute
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionCentre for Research on Management, Economy and Society
dc.contributor.institutionStatistical Services Consulting Unit
dc.contributor.institutionHealthcare Management and Policy Research Unit
dc.description.statusPeer reviewed
dc.relation.schoolHertfordshire Business School
dcterms.dateAccepted2013
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1007/s00148-012-0432-x
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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