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

Author

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  • Stergios Athanassoglou

    (European Commission Joint Research Center, Econometrics and Applied Statistics Unit)

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.

Suggested Citation

  • Stergios Athanassoglou, 2013. "Robust Multidimensional Welfare Comparisons: One Vector of Weights, One Vote," Working Papers 2013.40, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2013.40
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    References listed on IDEAS

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    1. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2013. "Measuring human development: a stochastic dominance approach," Journal of Economic Growth, Springer, vol. 18(1), pages 69-108, March.
    2. Anderson, Gordon & Crawford, Ian & Leicester, Andrew, 2011. "Welfare rankings from multivariate data, a nonparametric approach," Journal of Public Economics, Elsevier, vol. 95(3), pages 247-252.
    3. Kopylov, Igor, 2009. "Choice deferral and ambiguity aversion," Theoretical Economics, Econometric Society, vol. 4(2), June.
    4. James E. Foster & Mark McGillivray & Suman Seth, 2013. "Composite Indices: Rank Robustness, Statistical Association, and Redundancy," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 35-56, January.
    5. Giuseppe Munda & Michela Nardo, 2009. "Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting," Applied Economics, Taylor & Francis Journals, vol. 41(12), pages 1513-1523.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Multidimensional Welfare; Composite Index; e-Contamination; Polyhedral Geometry; Social Choice; Approximation Algorithms;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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