A geographically disaggregated analysis of multidimensional poverty in Punjab

Asim Iqbal, Anjum Siddiqui and Maryam Zafar

International Journal of Social Economics, 2020, vol. 47, issue 3, 365-383

Abstract: Purpose - The study seeks to examine the extent and the causes of multidimensional poverty as opposed to the traditional unidimensional headcount poverty measures to understand the true face of economic deprivation in Punjab, Pakistan. Design/methodology/approach - Poverty is measured through the Alkire–Foster index at the geographically disaggregated levels of divisions and districts, and the causes of pervasive poverty are analyzed through a logit model using the Multiple Indicators Cluster Survey (MICS) comprising of 95,238 households in 9 geographical divisions and their 36 districts. Findings - It was found that poverty in Punjab is associated with larger household size, inadequate wealth, and low levels of educational attainment, and that both matric as well as post-matric education reduced the chances of poverty of household heads by approximately 19 percent. In addition to rural poverty, the study finds evidence of urban poverty across the geographical districts of Punjab. Contrary to common belief that chances of poverty are higher in females, it was found to be more likely in males. However, the statistical significance of gender as a determinant of poverty was not observed in the majority of divisions. Practical implications - Practical implications were for focused policy interventions in poverty alleviation. Originality/value - The analysis of determinants of multidimensional poverty at the geographically disaggregated level of divisions is an original contribution. Peer review - The peer review history for this article is available at:https://publons.com/publon/10.1108/IJSE-01-2019-0037

Keywords: Logistic regression; Punjab; Multidimensional poverty; Deprivations (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijsepp:ijse-01-2019-0037

DOI: 10.1108/IJSE-01-2019-0037

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