Welfare Rankings From Multivariate Data, A Non-Parametric Approach

Gordon Anderson, Ian Crawford and Andrew Leicester ()

Working Papers from University of Toronto, Department of Economics

Abstract: Economic and Social Welfare is inherently multidimensional. However choosing a measure which combines several indicators is difficult and may have unintended and undesireable effects on the incentives for policymakers. We develope a nonparametric empirical method for deriving welfare rankings based on data envelopment which avoids the need to specify a weighting scheme. The results are valid for all possible social welfare functions which share certain cannonical properties. We apply this method to data on human development.

Keywords: Welfare Rankings; Data Envelopment; Human development (search for similar items in EconPapers)
JEL-codes: I3 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2010-01-14
New Economics Papers: this item is included in nep-ecm, nep-ltv and nep-mic
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Related works:
Journal Article: Welfare rankings from multivariate data, a nonparametric approach (2011)
Journal Article: Welfare rankings from multivariate data, a nonparametric approach (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:tor:tecipa:tecipa-386

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