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A multi-criteria fuzzy approach for analyzing poverty structure

Author

Listed:
  • 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)

Abstract

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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    Citations

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    Cited by:

    1. Alberto Arcagni & Laura Cavalli & Marco Fattore, 2021. "Partial Order Algorithms for the Assessment of Italian Cities Sustainability," Working Papers 2021.01, Fondazione Eni Enrico Mattei.
    2. Arcagni, Alberto & Cavalli, Laura & Fattore, Marco, 2021. "Partial Order Algorithms for the Assessment of Italian Cities Sustainability," FEEM Working Papers 309036, Fondazione Eni Enrico Mattei (FEEM).
    3. Alberto Arcagni & Elisa Barbiano di Belgiojoso & Marco Fattore & Stefania M. L. Rimoldi, 2019. "Multidimensional Analysis of Deprivation and Fragility Patterns of Migrants in Lombardy, Using Partially Ordered Sets and Self-Organizing Maps," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(2), pages 551-579, January.
    4. Iñaki Permanyer & M. Azhar Hussain, 2018. "First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of Different Approaches," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(3), pages 867-893, June.
    5. 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.
    6. Marco Fattore & Alberto Arcagni, 2019. "F-FOD: Fuzzy First Order Dominance Analysis and Populations Ranking Over Ordinal Multi-Indicator Systems," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(1), pages 1-29, July.
    7. 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.
    8. Lars Carlsen & Rainer Bruggemann, 2021. "Inequalities in the European Union—A Partial Order Analysis of the Main Indicators," Sustainability, MDPI, vol. 13(11), pages 1-22, June.
    9. Frauke Fuhrmann & Margit Scholl & Rainer Bruggemann, 2018. "How Can the Empowerment of Employees with Intellectual Disabilities Be Supported?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 1269-1285, April.

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