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Robust normative comparisons of socially risky situations

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  • Nicolas Gravel

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - École Centrale de Marseille - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université)

  • Benoît Tarroux

    (CREM - Centre de recherche en économie et management - CNRS - Centre National de la Recherche Scientifique - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - UNICAEN - Université de Caen Normandie - NU - Normandie Université)

Abstract

In this paper, we theoretically characterize robust empirically implementable normative criteria for evaluating socially risky situations. Socially risky situations are modeled as distributions, among individuals, of lotteries on a finite set of state-contingent pecuniary consequences. Individuals are assumed to have selfish Von Neumann-Morgenstern preferences for these socially risky situations. We provide empirically implementable criteria that coincide with the unanimity, over a reasonably large class of such individual preferences, of anonymous and Pareto-inclusive Von Neuman Morgenstern social rankings of risks. The implementable criteria can be interpreted as sequential expected poverty dominance.An illustration of the usefulness of the criteria for comparing the exposure to unemployment risk of different segments of the French and US workforce is also provided.

Suggested Citation

  • Nicolas Gravel & Benoît Tarroux, 2015. "Robust normative comparisons of socially risky situations," Post-Print halshs-01057024, HAL.
  • Handle: RePEc:hal:journl:halshs-01057024
    DOI: 10.1007/s00355-014-0833-8
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01057024
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    More about this item

    Keywords

    expected poverty; dominance; risk; Social welfare; unemployment;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D3 - Microeconomics - - Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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