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Graphical Representation of Multidimensional Poverty: Insights for Index Construction and Policy Making

Author

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  • Rodrigo García Arancibia

    (Universidad Nacional del Litoral
    Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET))

  • Ignacio Girela

    (Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
    Ciudad Universitaria, Córdoba)

Abstract

By means of probabilistic graphical models, in this paper, we present a new framework for exploring relationships among indicators commonly included in the Multidimensional Poverty Index (MPI). In particular, we propose an Ising model with covariates for modeling the MPI as an undirected graph. First, we prove why Ising models are consistent with the theoretical distribution of MPI indicators. Then, a comparison between our estimates and the association measures typically used in the literature is provided. Finally, we show how undirected graphs can complement the MPI policy-relevant properties, apart from discovering further insightful patterns that can be useful for policy purposes. This novel approach is illustrated with an empirical application for the global MPI indicators of Guinea and Ecuador, taking living areas and monetary poverty as covariates, respectively.

Suggested Citation

  • Rodrigo García Arancibia & Ignacio Girela, 2024. "Graphical Representation of Multidimensional Poverty: Insights for Index Construction and Policy Making," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 172(2), pages 595-634, March.
    • Handle: RePEc:spr:soinre:v:172:y:2024:i:2:d:10.1007_s11205-024-03325-8
    DOI: 10.1007/s11205-024-03325-8
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    More about this item

    Keywords

    MPI; Random Markov fields; Ising models; Conditional dependency; Deprivations;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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