MULTIDIMENSIONAL DECOMPOSITION OF POVERTY: A FUZZY SET APPROACH

This article extends the paper of Dagum C. and Costa M. (“Analysis and Measurement of Poverty. Univariate and Multivariate Approaches and their Policy Implications. A case of Study: Italy”, In Dagum C. and Ferrari G. (eds.), Household Behaviour, Equivalence Scales, Welfare and Poverty, Springer Verlag, Germany, 221-271, 2004). We further develop the study of multidimensional poverty using fuzzy sets by introducing a mixture of decomposition analysis. The model yields the most relevant dimensions of poverty (health, education, etc.) and the most relevant sub-groups (areas, gender, etc.) in order to identify the main forces that contribute to the overall amount of the state of poverty. The analysis of these results is useful for decision-makers that contemplate socio-economic policies in favour of poverty reduction. Finally, we apply this decomposition to study the level of poverty of Argentina in 1998.