Abstract
The major purpose of this study is to assess racial disparity and energy poverty index by measuring energy poverty index by using data envelopment analysis and regression equation from South Asia (2001-2018). An energy poverty index is quantifying the size and scope of energy poverty, and DEA is used to investigate the relevance of socioeconomic position to multidimensional energy poverty. In multidimensional energy poverty, location, house ownership position, number of dependents, and the age of the main caregiver have an important positive impact. Our research has shown that Bhutan is the most susceptible nation with an energy poverty index of (0.02), Maldives (0.03), and Bangladesh (0.11), while India (0.86) and Pakistan (0.49) are the least likely to be energy poor as regards energy poverty. Of the total energy production, 78% is based on traditional fuels, followed by 12% based on petroleum products. The Gini index indicates a positive association with the energy poverty index at a 5% significance level. This signifies that these socioeconomic indicators positively contribute to the energy poverty index level. This study developed more synchronized policies to eradicate energy poverty and can provide a way forward for policymakers to develop strategies to implement them suitably in the regional power sector.
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