A multi-criteria fuzzy approach for analyzing poverty structure
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Poverty is a fuzzy and complex phenomenon which is intrinsically multidimensional. First attempts
of tackling poverty with multidimensional measures trace back to the seventies with the conceptual
writings on income poverty by Amartya Sen (1976). Since then much research has been devoted to
answer questions of the type: (i) Who is poor? (ii) How poor is a poor? The measure of poverty
and social exclusion is certainly a key point in poverty description. While much effort has been put
in the last decades to the measurement of poverty, less attention has been paid to find relations
among different poverty aspects. In this paper, we start from a classical definition of the population
of the poor and we employ Fuzzy Multi-Criteria Analysis to provide an attempt to relate poverty aspects to one another, which we call a ‘structural representation of poverty’. Our focus is on the pattern of implications existing among different descriptors characterizing poverty aspects. We show how fuzzy relation theory and partially ordered set techniques are effective in representing complex relational structures and provide new insights into multidimensional poverty. As simple test cases the method is applied to data concerning two Italian regions based on EU-SILC database 2004.
Keywords: Multidimensional Poverty, Multi-criteria Analysis, Poverty Structure, Ordinal Variables, Posets, Fuzzy Quasi-order Relations. |
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