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dc.contributor.authorTofallis, C.
dc.date.accessioned2012-07-30T10:00:44Z
dc.date.available2012-07-30T10:00:44Z
dc.date.issued2012
dc.identifier.citationTofallis , C 2012 ' An automatic-democratic approach to weight setting for the new human development index ' UH Business School Working Paper , University of Hertfordshire , pp. 32 .
dc.identifier.otherORCID: /0000-0001-6150-0218/work/34655898
dc.identifier.urihttp://hdl.handle.net/2299/8738
dc.descriptionFinal version of the paper has been accepted for publication in Journal of Population Economics
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.extent864961
dc.language.isoeng
dc.publisherUniversity of Hertfordshire
dc.relation.ispartof
dc.relation.ispartofseriesUH Business School Working Paper
dc.titleAn automatic-democratic approach to weight setting for the new human development indexen
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionSocial Sciences, Arts & Humanities Research Institute
dc.contributor.institutionCentre for Research on Management, Economy and Society
dc.contributor.institutionStatistical Services Consulting Unit
dc.contributor.institutionDepartment of Marketing and Enterprise
rioxxterms.typeWorking paper
herts.preservation.rarelyaccessedtrue


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