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Una Aplicación Del Análisis Factorial Múltiple Para El Estudio De La Pobreza Multidimensional En Uruguay (An Application Of Multiple Factorial Analysis For The Study Of Multidimensional Poverty In Uruguay)

Author

Listed:
  • Saldaña, Maximiliano
  • Nalbarte, Laura
  • Álvarez-Vaz, Ramón Dr.

    (Universidad de la República)

Abstract

La medición de la pobreza multidimensional ha sido un tema de interés tanto en el marco internacional como el nacional. En el presente trabajo se explora el Análisis Factorial Múltiple -AFM- (Escofier y Pages, 1994) como una opción para resumir la información relativa a las distintas dimensiones de la pobreza. Se busca llegar a una propuesta de un ı́ndice de pobreza multidimensional basado en el AFM como una alternativa al empleado por la Organización de las Naciones Unidas. La metodologı́a que se aplica es considerada particularmente pertinente para el objetivo dada su capacidad de resumir información de conjuntos extensos de variables, que son ponderados apropiadamente para obtener como resultado final un conjunto menor de nuevas variables, con la menor pérdida de variabilidad explicada posible. A su vez, esta metodologı́a permite visualizar vı́nculos entre las variables y entre las distintas dimensiones de la pobreza. Se hace uso de bases de datos de la Encuesta de Gastos e Ingresos de los Hogares 2016-2017, realizada por el Instituto Nacional de Estadı́stica en Uruguay. Abstract The measurement of multidimensional poverty has been a topic of interest both in the international and national framework. In this paper, Multiple Factor Analysis -AFM- (Escofier and Pages, 1994) is explored as an option for summarize the information related to the different dimensions of poverty. It seeks to arrive at a proposal for an index of multidimensional poverty based on the AFM as an alternative to the one used by the United Nations Organization. The methodology that is applied is considered particularly pertinent to the objective given its ability to summarize information from extensive sets of variables, which are appropriately weighted to obtain as a final result a smaller set of new variables, with the least possible loss of explained variability. In turn, this methodology makes it possible to visualize links between the variables and between the different dimensions of poverty. Use is made of databases from the Household Expenditure and Income Survey 2016-2017, carried out by the National Institute of Statistics in Uruguay.

Suggested Citation

  • Saldaña, Maximiliano & Nalbarte, Laura & Álvarez-Vaz, Ramón Dr., 2022. "Una Aplicación Del Análisis Factorial Múltiple Para El Estudio De La Pobreza Multidimensional En Uruguay (An Application Of Multiple Factorial Analysis For The Study Of Multidimensional Poverty In Uru," OSF Preprints 7sqvc, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:7sqvc
    DOI: 10.31219/osf.io/7sqvc
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    References listed on IDEAS

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    1. Escofier, B. & Pages, J., 1994. "Multiple factor analysis (AFMULT package)," Computational Statistics & Data Analysis, Elsevier, vol. 18(1), pages 121-140, August.
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