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

Rodrigo García Arancibia and Ignacio Girela
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Ignacio Girela: Universidad Nacional de Córdoba/CONICET

No 233, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)

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

Keywords: MPI; Markov Random Fields; Ising Model; Conditional Dependency; Deprivations (search for similar items in EconPapers)
JEL-codes: C18 C35 I3 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2023-04
New Economics Papers: this item is included in nep-ecm
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https://rednie.eco.unc.edu.ar/files/DT/233.pdf (application/pdf)

Related works:
Journal Article: Graphical Representation of Multidimensional Poverty: Insights for Index Construction and Policy Making (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:233

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