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

Author

Listed:
  • Rodrigo García Arancibia

    (Universidad Nacional del Litoral/CONICET)

  • Ignacio Girela

    (Universidad Nacional de Córdoba/CONICET)

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, 2023. "Graphical Representation of Multidimensional Poverty: Insights for Index Construction and Policy Making," Working Papers 233, Red Nacional de Investigadores en Economía (RedNIE).
  • Handle: RePEc:aoz:wpaper:233
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    File URL: https://rednie.eco.unc.edu.ar/files/DT/233.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    MPI; Markov Random Fields; Ising Model; 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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