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A fuzzy logic approach to poverty analysis based on the Gini and Bonferroni inequality indices

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Abstract

In the poverty analysis framework, a great deal of attention has been paid to the poverty measurement in terms of monetary variables, such as income or consumption. In this context, a relevant open problem is connected with the distinction between poor and non-poor. In fact, the concept of poverty is rather vague and cannot be defined in a clear way. In this respect, following a fuzzy logic approach, some new poverty measures are proposed. In particular, the fuzzy extension of two existing poverty measures based on the Gini and Bonferroni inequality indices is provided. Some synthetic and real applications are given in order to show how the proposed poverty measures work.

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Authors and Affiliations

  1. Dipartimento di Statistica, Probabilità e Statistiche Applicate, Sapienza Università di Roma, P.le Aldo Moro, 5, 00185, Rome, Italy

    Paolo Giordani & Giovanni Maria Giorgi

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  1. Paolo Giordani
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  2. Giovanni Maria Giorgi
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Correspondence to Paolo Giordani.

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Giordani, P., Giorgi, G.M. A fuzzy logic approach to poverty analysis based on the Gini and Bonferroni inequality indices. Stat Methods Appl 19, 587–607 (2010). https://doi.org/10.1007/s10260-010-0146-8

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  • DOI: https://doi.org/10.1007/s10260-010-0146-8

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