Robust Multidimensional Welfare Comparisons: One Vector of Weights, One Vote

Stergios Athanassoglou
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Stergios Athanassoglou: European Commission Joint Research Center, Econometrics and Applied Statistics Unit
Authors registered in the RePEc Author Service: Stergios Athanasoglou

No 2013.40, Working Papers from Fondazione Eni Enrico Mattei

Abstract: Many aspects of social welfare are intrinsically multidimensional. Composite indices at-tempting to reduce this complexity to a unique measure abound in many areas of economics and public policy. Comparisons based on such measures depend, sometimes critically, on how the different dimensions of performance are weighted. Thus, a policy maker may wish to take into account imprecision over composite index weights in a systematic manner. In this paper, such weight imprecision is parameterized via the e-contamination framework of Bayesian statistics. Subsequently, combining results from polyhedral geometry, social choice, and theoretical computer science, an analytical procedure is presented that yields a provably robust ranking of the relevant alternatives in the presence of weight imprecision. The main idea is to consider a vector of weights as a voter and a continuum of weights as an electorate. The procedure is illustrated on recent versions of the Rule of Law and Human Development indices.

Keywords: Multidimensional Welfare; Composite Index; e-Contamination; Polyhedral Geometry; Social Choice; Approximation Algorithms (search for similar items in EconPapers)
JEL-codes: C02 C61 D04 D71 I31 (search for similar items in EconPapers)
Date: 2013-05
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Working Paper: Robust Multidimensional Welfare Comparisons: One Vector of Weights, One Vote (2013)
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