Inequalities in multidimensional poverty: evidence from Argentina

Abstract

This article presents a new synthetic methodology that gauges simultaneously the inequalities in multidimensional poverty within and between groups of population and the dimensions that tend to increase inequality in poverty.

Notes

¹ Let A = {a ₁, … , a_i , … , a_n } be the population set object of research, where n is the cardinality of A.

² X = (X ₁, … , X_j , … , X_m ) is the vector of selected attributes.

³ A necessary condition to satisfy the subgroup decomposition is that each subgroup must have the same values for the weights associated to the dimensions. Hence, subgroups comparisons are possible. See Mussard and Pi Alperin (2005) for more details.

⁴ See the methodology proposed by Mussard (2004).

⁵ Upon the request of the authors, the determination of the poverty index and the degree of membership can be obtained.

Table 1. Overall decomposition of poverty inequalities^a

⁶ With 17.92% of poor households. This value was calculated using the multidimensional approach of fuzzy sets.

Table 2. Within-group inequalities of poverty^a

⁷ With this method, we can easily calculate the relative contribution of each one of the dimensions and each region to the global within-group and between-group inequalities.

⁸ Viewed as the richest one, with 14.14% of poor households.

Table 3. Between-group inequalities of poverty^a