Robust normative comparisons of socially risky situations

International audienceIn 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

Robust Normative Comparisons of Socially Risky Situations

In this paper, we characterize and empirically implement robust normative criteria for comparing societies on the basis of their allocations of risks among their members. Risks are modelled as lotteries on the set of distributions of state-contingent pecuniary consequences. Individuals are assumed to have individualistic Von Neuman-Morgenstern preferences for these risks. Appealing to Harsanyi’s aggregation theorem, we provide empirically implementable criteria that coincide with the unanimity, over all such individual preferences, of anonymous and Pareto-inclusive Von Neuman Morgenstern social rankings of risks. The empirically implementable criteria can be interpreted as sequential expected poverty dominance. Illustrations of the usefulness of the criteria for comparing the exposure to unemployment risk of different segments of the French and US workforce and for appraising the evolution, over time, of risks of violent crimes in India are also provided.Risk, Dominance, ex-ante Social Welfare, Expected Poverty, Unemployment, Crime.