Welfare rankings from multivariate data, a nonparametric approach
AbstractEconomic and social welfare is inherently multidimensional. However, choosing a measure which combines several indicators is difficult and may have unintendend and undesirable effects on the incentives of policy makers. We develop a nonparametric empirical method for deriving welfare rankings for a social planner based on data envelopment, which avoids the need to specify a weighting scheme. We apply this method to data on Human Development.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Public Economics.
Volume (Year): 95 (2011)
Issue (Month): 3 ()
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Web page: http://www.elsevier.com/locate/inca/505578
Welfare; Nonparametric methods;
Other versions of this item:
- Anderson, Gordon & Crawford, Ian & Leicester, Andrew, 2011. "Welfare rankings from multivariate data, a nonparametric approach," Journal of Public Economics, Elsevier, Elsevier, vol. 95(3-4), pages 247-252, April.
- Gordon Anderson & Ian Crawford & Andrew Leicester, 2010. "Welfare Rankings From Multivariate Data, A Non-Parametric Approach," Working Papers tecipa-386, University of Toronto, Department of Economics.
- I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
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