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Multidimensional welfare rankings under weight imprecision: a social choice perspective

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  • Stergios Athanassoglou

Abstract

Ranking alternatives based on multidimensional welfare indices depends, sometimes critically, on how the different dimensions of welfare are weighted. In this paper, a theoretical framework is presented that yields a set of consensus rankings in the presence of such weight imprecision. The main idea is to consider a vector of weights as an imaginary voter submitting preferences over alternatives. With this voting construct in mind, the well-known Kemeny rule from social choice theory is introduced as a means of aggregating the preferences of many plausible choices of weights, suitably weighted by the importance attached to them. The axiomatic characterization of Kemeny’s rule due to Young and Levenglick ( 1978 ) and Young ( 1988 ) extends to the present context. An analytic solution is derived for an interesting special case of the model corresponding to generalized weighted means and the $$\epsilon $$ ϵ -contamination framework of Bayesian statistics. The model is applied to the ARWU index of Shanghai University. Graph-theoretic insights are shown to facilitate computation significantly. Copyright European Union 2015

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  • Stergios Athanassoglou, 2015. "Multidimensional welfare rankings under weight imprecision: a social choice perspective," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 44(4), pages 719-744, April.
    • Handle: RePEc:spr:sochwe:v:44:y:2015:i:4:p:719-744
    DOI: 10.1007/s00355-014-0858-z
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    Cited by:

    1. Lucio Esposito & Enrica Chiappero‐Martinetti, 2019. "Eliciting, Applying And Exploring Multidimensional Welfare Weights: Evidence From The Field," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(S1), pages 204-227, November.
    2. Aleksandras KRYLOVAS & Natalja KOSAREVA & Edmundas Kazimieras ZAVADSKAS, 2016. "Statistical Analysis of KEMIRA Type Weights Balancing Methods," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 19-39, September.
    3. Mero-Figueroa, Marina & Galdeano-Gómez, Emilio & Piedra-Muñoz, Laura & Obaco, Moisés, 2020. "Measuring well-being: A Buen Vivir (living well) indicator for Ecuador," MPRA Paper 119912, University Library of Munich, Germany.
    4. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    5. Marina Mero-Figueroa & Emilio Galdeano-Gómez & Laura Piedra-Muñoz & Moisés Obaco, 2020. "Measuring Well-Being: A Buen Vivir (Living Well) Indicator for Ecuador," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 265-287, November.
    6. Burhan Can Karahasan & Fırat Bilgel, 2021. "The Topography and Sources of Multidimensional Poverty in Turkey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 413-445, April.
    7. Athanasoglou, Stergios & Bosetti, Valentina & Drouet, Laurent, 2017. "A Simple Framework for Climate-Change Policy under Model Uncertainty," MITP: Mitigation, Innovation and Transformation Pathways 254043, Fondazione Eni Enrico Mattei (FEEM).
    8. Mehmet Pinar, 2022. "Choquet-Integral Aggregation Method to Aggregate Social Indicators to Account for Interactions: An Application to the Human Development Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 1-53, January.
    9. Francesco Tajani & Maria Rosaria Guarini & Francesco Sica & Rossana Ranieri & Debora Anelli, 2022. "Multi-Criteria Analysis and Sustainable Accounting. Defining Indices of Sustainability under Choquet’s Integral," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    10. Mehmet Pinar, 2019. "Multidimensional Well-Being and Inequality Across the European Regions with Alternative Interactions Between the Well-Being Dimensions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(1), pages 31-72, July.
    11. Argyris, Nikolaos & Østerdal, Lars Peter & Hussain, M. Azhar, 2023. "Value-driven Multidimensional Welfare Analysis: A Dominance Approach with Application to Comparisons of European Populations," Working Papers 12-2023, Copenhagen Business School, Department of Economics.
    12. Miftakhova, Alena, 2021. "Global sensitivity analysis for optimal climate policies: Finding what truly matters," Economic Modelling, Elsevier, vol. 105(C).

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    More about this item

    Keywords

    D71; D72; I31; C61;
    All these keywords.

    JEL classification:

    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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