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One-dimensional Fuzzy Poverty Measure from an Bootstrap Method Perspective

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  • Belhadj BESMA

    (ISG, University of Tunis Tunisia)

Abstract

This paper is a contribution to the analysis of deprivation seen as a one-dimensional condition. A most useful tool for such analysis is to view deprivation as a matter of degree, giving a quantitative expression to its intensity for individuals. Such ‘fuzzy’ conceptualisation has been increasingly utilised in poverty and deprivation research. This paper aims to further develop and refine this strand of research. The concern of the paper is primarily methodological rather than detailed numerical analysis from particular applications. We re-examine the two additional aspects introduced by the use of fuzzy (as distinct from the conventional poor/non-poor dichotomous) measures, namely: the choice of membership functions and the choice of rules for the manipulation of the resulting fuzzy sets, rules defining their intersection and averaging. The relationship of the proposed fuzzy monetary measure with the membership function and an estimate, by confidence interval, of the poverty line.

Suggested Citation

  • Belhadj BESMA, 2010. "One-dimensional Fuzzy Poverty Measure from an Bootstrap Method Perspective," EuroEconomica, Danubius University of Galati, issue 24, pages 110-125, March.
    • Handle: RePEc:dug:journl:y:2010:i:24:p:110-125
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    File URL: http://journals.univ-danubius.ro/index.php/euroeconomica/article/view/272/255
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    References listed on IDEAS

    as
    1. Buhong Zheng, 1997. "Aggregate Poverty Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 11(2), pages 123-162, June.
    2. Gianni Betti & Bruno Cheli & Vijay Verma, 2006. "On longitudinal analysis of poverty conceptualised as a fuzzy state," Working Papers 32, ECINEQ, Society for the Study of Economic Inequality.
    3. Gianni Betti & Bruno Cheli & Riccardo Cambini, 2004. "A statistical model for the dynamics between two fuzzy states: theory and an application to poverty analysis," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 391-411.
    4. Achille Lemmi & Gianni Betti (ed.), 2006. "Fuzzy Set Approach to Multidimensional Poverty Measurement," Economic Studies in Inequality, Social Exclusion, and Well-Being, Springer, number 978-0-387-34251-1, July.
    5. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    6. Bruno Cheli & Gianni Betti, 1999. "Fuzzy analysis of poverty dynamics on an italian pseudo panel 1985-1994," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 85-105.
    7. Ravallion, Martin & Bidani, Benu, 1994. "How Robust Is a Poverty Profile?," The World Bank Economic Review, World Bank, vol. 8(1), pages 75-102, January.
    8. Sara Lelli, 2001. "Factor Analysis vs. Fuzzy Sets Theory: Assessing the Influence of Different Techniques on Sen's Functioning Approach," Public Economics Working Paper Series ces0121, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
    9. repec:bla:jecsur:v:11:y:1997:i:2:p:123-62 is not listed on IDEAS
    10. A. Atkinson, 2003. "Multidimensional Deprivation: Contrasting Social Welfare and Counting Approaches," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 1(1), pages 51-65, April.
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