Inequalities In Poverty: Evidence From Argentina

In 1990, Cerioli and Zani introduced an operational multivariate method to analyse and measure poverty, aiming at incorporating several dimensions of poverty. As Dagum and Costa [2004] showed, this study applies the fuzzy set theoretic approach and thus making quantitatively operational the French Social Exclusion Theory and Sen’s analysis of functioning and capability. The literature offers many ways to deal with inequalities in poverty. The most common approach is those of Amartya Sen [1976] with the Gini index of poverty gap ratio, that is, a fundamental component of Sen’s poverty index. The problem is that this Gini index does not offer any information on the determinants of the inequalities. For this purpose, Mussard [2004] introduced the bidimensional decomposition of the Gini ratio, where both sub-groups and income sources are jointly analysed in a decomposition context. These two methodologies are combined in order to evaluate the differences in multidimensional poverty within and between sub-groups of population, and to determine the dimensions that tend to increase inequality in poverty. The goal of this article is double. Firstly, we present the combined methodology to study the inequality in multidimensional poverty. Secondly, we apply this technique to analyse the differences in poverty within and between the six principal regions of Argentina.