In this paper, we introduce and analyze a class of fuzzy poverty measures based on exponential means. Since poverty is a vague notion, individuals should not be classified in poor or non-poor. In our proposal, we have associated a degree of poverty to each income through a fuzzy membership function. We have extended normalized gaps from the classical approach, where poverty is a dichotomous notion, to the fuzzy setting. The proposed family of fuzzy poverty measures decomposes into the three I’s indicators: the incidence of poverty is captured through the headcount ratio, while intensity and inequality of poverty are measured by the core and the remainder, respectively, of a parameterized exponential mean over the normalized gaps of (somewhat) poor individuals. Taking into account the features of the dual decomposition of exponential means, we provide some properties of the proposed fuzzy poverty measures.

A new class of fuzzy poverty measures

Marques Pereira, Ricardo Alberto;
2015-01-01

Abstract

In this paper, we introduce and analyze a class of fuzzy poverty measures based on exponential means. Since poverty is a vague notion, individuals should not be classified in poor or non-poor. In our proposal, we have associated a degree of poverty to each income through a fuzzy membership function. We have extended normalized gaps from the classical approach, where poverty is a dichotomous notion, to the fuzzy setting. The proposed family of fuzzy poverty measures decomposes into the three I’s indicators: the incidence of poverty is captured through the headcount ratio, while intensity and inequality of poverty are measured by the core and the remainder, respectively, of a parameterized exponential mean over the normalized gaps of (somewhat) poor individuals. Taking into account the features of the dual decomposition of exponential means, we provide some properties of the proposed fuzzy poverty measures.
2015
Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
Amsterdam
Atlantis Press
978-94-62520-77-6
J. L., García Lapresta; C., Lasso de la Vega; Marques Pereira, Ricardo Alberto; A., Urrutia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/101366
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