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Fuzzy poverty measurement: multidimensional and unidimensional indicators

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  • Michele Costa

Abstract

This paper proposes a comparison between multidimensional and unidimensional poverty indicators. Sets of poor units identified by traditional head count ratio, fuzzy unidimensional and fuzzy multidimensional indices are compared by means of a rank correlation analysis. The robustness of the comparison is ensured by a simulation study, which allows to address several issues related not only to fuzzy sets based methods, such as the subjective choice of membership to the poor set, but also to the multidimensional measurement, such as the effect of the weighting system. Our results stress that the unidimensional indicators provide partial information on poverty condition.

Suggested Citation

  • Michele Costa, 2020. "Fuzzy poverty measurement: multidimensional and unidimensional indicators," Working Papers wp1156, Dipartimento Scienze Economiche, Universita' di Bologna.
    • Handle: RePEc:bol:bodewp:wp1156
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    References listed on IDEAS

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    1. Walter Bossert & Satya R. Chakravarty & Conchita D’Ambrosio, 2019. "Multidimensional Poverty and Material Deprivation with Discrete Data," Themes in Economics, in: Satya R. Chakravarty (ed.), Poverty, Social Exclusion and Stochastic Dominance, pages 191-209, Springer.
    2. Rolf Aaberge & Andrea Brandolini, 2014. "Multidimensional poverty and inequality," Discussion Papers 792, Statistics Norway, Research Department.
    3. Alkire, Sabina & Santos, Maria Emma, 2014. "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index," World Development, Elsevier, vol. 59(C), pages 251-274.
    4. Francesco Andreoli & Claudio Zoli, 2020. "From unidimensional to multidimensional inequality: a review," METRON, Springer;Sapienza Università di Roma, vol. 78(1), pages 5-42, April.
    5. 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.
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    More about this item

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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