Investigation of multidimensional poverty in Pakistan at the national, regional, and provincial level

Wajiha Haq (), Mir Azam, Zaki Babar, Saad Amir and Fareyha Said
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Wajiha Haq: School of Social Sciences and Humanities
Mir Azam: School of Social Sciences and Humanities
Zaki Babar: School of Social Sciences and Humanities
Saad Amir: School of Social Sciences and Humanities
Fareyha Said: University of Malaya

Palgrave Communications, 2024, vol. 11, issue 1, 1-9

Abstract: Abstract To achieve the sustainable development goal of “no poverty”, many attempts have been made to measure poverty so that policy intervention can target the right people with the correct intensity. Since the traditional method of a unidimensional approach using monetary indicators, such as income and consumption, is now considered insufficient, a multidimensional approach has been employed using non-monetary indicators. The latter approach encompasses the different poverty aspects affecting an individual’s capabilities and functioning. This study aimed to calculate multidimensional poverty in Pakistan using the Alkire & Foster method and Pakistan Social and Living Standards Measurement (PSLM) published by the Pakistan Bureau of Statistics data for 2018–19. To further complete the research, a binary logistic regression has been run to measure the effects of a deviation in income status on multidimensional poverty to see the impact of monetary income on non-monetary measures. Results show that the national global Multidimensional Poverty Index (MPI) is 0.24, meaning that multidimensionally poor people in Pakistan experience 24% of the total deprivations. The most deprived dimension of the three is education (44.7%), which needs special attention. Furthermore, if a household’s total annual income increases and becomes more significant than the mean income of the sample, the household’s probability of being multidimensionally poor will decrease. This implies that with the increase in average national income, the national poverty will reduce not only in absolute terms but also multidimensionally. This study’s findings have several implications for policymakers, and the results of the MPI should align the allocation of public sector resources calculated to give a geographical and sectoral image of the poverty situation, which will guide policy designs and allocation of budget and resources.

Date: 2024
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DOI: 10.1057/s41599-024-03005-5

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