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A multi-criteria fuzzy approach for analyzing poverty structure


  • Paola Annoni

    (University of Milan, Dept. of Economics, Business and Statistics)

  • Marco Fattore

    (University of Milano-Bicocca, Dept. of Statistics)

  • Rainer Brüggemann

    (Institute of Fresh Water Ecology and Inland Fisheries, Berlin, Germany)


Poverty is a multidimensional, fuzzy and complex phenomenon that cannot be faithfully represented by mono-dimensional monetary indicators. In the last years, much research has been devoted to tackle poverty fuzziness, while less attention has been paid to poverty complexity. In this paper, we employ Fuzzy Multi-Criteria Analysis to provide a structural representation of poverty, in terms of the pattern of implications existing among different poverty descriptors related to specific scenarios. 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. An application of Fuzzy Multi-Criteria Analysis to poverty data concerning two Italian regions is also provided, based on EU-SILC data for year 2004.

Suggested Citation

  • Paola Annoni & Marco Fattore & Rainer Brüggemann, 2008. "A multi-criteria fuzzy approach for analyzing poverty structure," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1072, Universitá degli Studi di Milano.
  • Handle: RePEc:bep:unimip:unimi-1072
    Note: oai:cdlib1:unimi-1072

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    Cited by:

    1. Marco Fattore, 2016. "Partially Ordered Sets and the Measurement of Multidimensional Ordinal Deprivation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(2), pages 835-858, September.
    2. Rainer Bruggemann & Lars Carlsen, 2015. "Incomparable: what now II? Absorption of incomparabilities by a cluster method," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1633-1645, July.


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