{"title":"Graphical Representation of Multidimensional Poverty: Insights for Index Construction and Policy Making","authors":"Rodrigo García Arancibia, Ignacio Girela","doi":"10.1007/s11205-024-03325-8","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":21943,"journal":{"name":"Social Indicators Research","volume":"27 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Indicators Research","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1007/s11205-024-03325-8","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
Since its foundation in 1974, Social Indicators Research has become the leading journal on problems related to the measurement of all aspects of the quality of life. The journal continues to publish results of research on all aspects of the quality of life and includes studies that reflect developments in the field. It devotes special attention to studies on such topics as sustainability of quality of life, sustainable development, and the relationship between quality of life and sustainability. The topics represented in the journal cover and involve a variety of segmentations, such as social groups, spatial and temporal coordinates, population composition, and life domains. The journal presents empirical, philosophical and methodological studies that cover the entire spectrum of society and are devoted to giving evidences through indicators. It considers indicators in their different typologies, and gives special attention to indicators that are able to meet the need of understanding social realities and phenomena that are increasingly more complex, interrelated, interacted and dynamical. In addition, it presents studies aimed at defining new approaches in constructing indicators.
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