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Multidimensional Decomposition Of Poverty: A Fuzzy Set Approach

  • Stéphane Mussard


    (GREDI, Université de Sherbrooke and Université de Perpignan)

  • Pi Alperin María Noel


    (LAMETA, Université Montpellier I)

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.

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Paper provided by Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke in its series Cahiers de recherche with number 05-08.

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Length: 26 pages
Date of creation: 2005
Date of revision:
Handle: RePEc:shr:wpaper:05-08
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