Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/74813
Authors: 
Athanassoglou, Stergios
Year of Publication: 
2013
Series/Report no.: 
Nota di Lavoro, Fondazione Eni Enrico Mattei 40.2013
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 di erent dimensions of performance are weighted. Thus, a policy maker 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 -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.
Subjects: 
Multidimensional Welfare
Composite Index
ε-contamination
Polyhedral Geometry
Social Choice
Approximation Algorithms
JEL: 
C02
C61
D04
D71
I31
Document Type: 
Working Paper

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