The indicators measuring socioeconomic wellbeing, such as the human development index (HDI) and multi‐dimensional poverty indicator (MPI), recognize energy as an important resource for human development. However, energy did not find due weight in determining HDI or MPI, except as a fractional contributor to MPI calculations. This study presents a regression model to establish an energy–poverty nexus in Pakistan, utilizing a real‐world dataset. Defining poverty in terms of per‐capita income (PCI), the proposed model incorporates education‐based parameters along with the energy‐dependent indicators linked to households in Pakistan. The data aggregated at districts level are extracted from the Census 2017 campaign, Pakistan Bureau of Statistics (PBS). Statistical analyses indicate that energy‐based identifiers correlate well with the PCI and augment the education‐only model, capturing 94% variability in PCI vs. 78% for the education‐only model. The study highlights the criticality of relevant data collection and data‐driven planning in Pakistan for creating synergy in energy planning and poverty alleviation programs and provides recommen-dations for considering energy as an important and integral contributory factor in the human development index (HDI).
Bibliographical note© 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
- Developing countries
- Energy–poverty nexus
- Human development index
- Regression analysis