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Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality

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  • Davidson, Russell
  • Duclos, Jean-Yves

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Abstract

We derive the asymptotic sampling distribution of various estimators frequently used to order distributions in terms of poverty, welfare and inequality. This includes estimators of most of the poverty indices currently in use, as well as estimators of the curves used to infer stochastic dominance of any order. These curves can be used to determine whether poverty, inequality or social welfare is greater in one distribution than in another for general classes of indices. We also derive the sampling distribution of the maximal poverty lines (or income censoring thresholds) up to which we may confidently assert that poverty or social welfare is greater in one distribution than in another. The sampling distribution of convenient estimators for dual approaches to the measurement of poverty is also established. The statistical results are established for deterministic or stochastic poverty lines as well as for paired or independent samples of incomes. Our results are briefly illustrated using data for 6 countries drawn from the Luxembourg Income Study data bases. On étudie les propriétés asymptotiques de plusieurs estimateurs fréquemment utilisés pour ordonner les répartitions de revenus en termes de pauvreté, bien-être social, et inégalité. Ces estimateurs incluent les estimateurs de la plupart des indices de pauvreté couramment en usage ainsi que les estimateurs des courbes utiles pour l'inférence de la dominance stochastique de n'importe quel ordre. Ces courbes nous permettent de déterminer si la pauvreté, l'inégalité ou le bien-être social sont plus élevés dans une répartition que dans une autre pour des classes générales d'indices. On étudie aussi la distribution échantillonnale des seuils maximum de pauvreté ou de censure des revenus jusqu'auxquels on peut affirmer sans ambiguïté que la pauvreté ou le bien-être social sont plus élevés dans une répartition de revenus que dans une autre. La distribution échantillonnale d'estimateurs pour l'approche duale à la mesure de la pauvreté est aussi dérivée. Les résultats statistiques s'appliquent à des seuils déterministes ou stochastiques et à des échantillons dépendants ou indépendants. On illustre brièvement nos résultats à l'aide de données sur 6 pays tirées des banques de données du Luxembourg Income Study.

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Bibliographic Info

Paper provided by Université Laval - Département d'économique in its series Cahiers de recherche with number 9805.

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Date of creation: 1998
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Handle: RePEc:lvl:laeccr:9805

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Keywords: Stochastic Dominance; Poverty; Inequality; Relative and Critical Poverty Lines; Distribution-free statistical inference; Dominance stochastique; Pauvreté; Inégalité; Seuils de pauvreté relatifs et critiques; Inférence statistique robuste;

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