Multidimensional poverty index across districts in Punjab, Pakistan: estimation and rationale to consolidate with SDGs

Tabish Nawab (), Saqlain Raza (), Malik Shahzad Shabbir (), Ghulam Khan and Sana Bashir ()
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Tabish Nawab: Ibn Haldun University
Saqlain Raza: Imam Abdulrahman Bin Faisal University
Malik Shahzad Shabbir: Ibn Haldun University
Sana Bashir: Governance and Public Policy, National Defence University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 2, No 13, 1325 pages

Abstract: Abstract Multidimensional poverty index (MPI) has gotten relevance of their public policy and arguably became a strong instrument to meet sustainable development goals (SDGs). This study proposes measurement of MPI along with its components that are responsible for a change in MPI over the period from 2007 to 2018 using the Alkire–Foster method. Four rounds of multiple indicators cluster survey have been used which is only available data to account for all of the dimensions of MPI. The findings show the incidence of MPI in Punjab has downturned by an annual average of 1.1%, from 10% of the population in 2007 to 6.7% of the population in 2018. Southern Punjab is poorer than North-Central Punjab. The magnitude of poverty is lower in industrialized districts which are mainly situated in northern Punjab. Health and education dimensions need to be improved throughout the province. In the living standard dimension, cooking fuel, flooring, and sanitation need to be administered. Globally, MPI is a great poverty measurement and monitoring tool that determines the pace and progress in SDGs categorically. Due to its multidimensional structure, MPI is specifically attributed to measure the SDG # 1, 2, 3, 4, 6, 7, and 11.

Keywords: Punjab; Multidimensional poverty; Alkire–Foster method (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-021-02095-4

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