Medición de la pobreza multidimensional en México mediante un análisis bibliométrico y de ecuaciones estructurales

Objective. Multidimensional poverty in Mexico was measured through a bibliometric and structural equation analysis. Design/Methodology/Approach. We used the technique developed by the National Council for the Evaluation of Social Development Policy (CONEVAL, in Spanish) in Mexico, based on information from the National Household Income and Expenditure Survey (ENIGH, in Spanish). The Smart PLS software also used the partial least squares (PLS) technique. Regarding the bibliometric part, a descriptive analysis was performed using the Scopus database and VOSviewer as a processing tool. Results/Discussion. The results showed that basic housing services, access to food, quality, housing spaces, and income significantly impact multidimensional poverty. The PLS model showed adequate predictive superiority and goodness of fit. From the bibliometric point of view, there was clear interest on the part of the academic and scientific community in developing knowledge in this field. Conclusions. The effectiveness of the PLS model for measuring multidimensional poverty in Mexico is demonstrated, and several determinants are highlighted. Future studies are recommended to improve social policies and poverty reduction strategies. Originality/Value. The study provides a novel approach by using the PLS model to measure multidimensional poverty in Mexico. It applies a robust exploratory methodology that can be replicated in similar contexts and is supported by bibliometric contrast.

Authors

Publication Details

Journal
Iberoamerican Journal of Science Measurement and Communication
Published
2024-10-13
DOI
https://doi.org/10.47909/ijsmc.1354
Citations
2
Primary Topic
Income, Poverty, and Inequality
Type
article
Field-Weighted Citation Impact
2.26
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article

Medición de la pobreza multidimensional en México mediante un análisis bibliométrico y de ecuaciones estructurales

Flor de María García Martínez, Víctor Hugo Bañuelos García, Blanca Isabel Llamas Félix, Reina Margarita Vega Esparza
2 citations
Iberoamerican Journal of Science Measurement and Communication
Income, Poverty, and Inequality
2.26
article

Medición de la pobreza multidimensional en México mediante un análisis bibliométrico y de ecuaciones estructurales

Flor de María García Martínez, Víctor Hugo Bañuelos García, Blanca Isabel Llamas Félix, Reina Margarita Vega Esparza
article en
2 citations

Abstract

Objective. Multidimensional poverty in Mexico was measured through a bibliometric and structural equation analysis. Design/Methodology/Approach. We used the technique developed by the National Council for the Evaluation of Social Development Policy (CONEVAL, in Spanish) in Mexico, based on information from the National Household Income and Expenditure Survey (ENIGH, in Spanish). The Smart PLS software also used the partial least squares (PLS) technique. Regarding the bibliometric part, a descriptive analysis was performed using the Scopus database and VOSviewer as a processing tool. Results/Discussion. The results showed that basic housing services, access to food, quality, housing spaces, and income significantly impact multidimensional poverty. The PLS model showed adequate predictive superiority and goodness of fit. From the bibliometric point of view, there was clear interest on the part of the academic and scientific community in developing knowledge in this field. Conclusions. The effectiveness of the PLS model for measuring multidimensional poverty in Mexico is demonstrated, and several determinants are highlighted. Future studies are recommended to improve social policies and poverty reduction strategies. Originality/Value. The study provides a novel approach by using the PLS model to measure multidimensional poverty in Mexico. It applies a robust exploratory methodology that can be replicated in similar contexts and is supported by bibliometric contrast.

Iberoamerican Journal of Science Measurement and CommunicationVol. 4(2)
No poverty
Openalex Percentile: Top 10%
Income, Poverty, and Inequality
2.26
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