2021
DOI: 10.3390/su131910969
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Measuring Energy Poverty and Its Impact on Economic Growth in Pakistan

Abstract: During the last two decades, energy poverty has captured the growing attention of researchers and policymakers due to its strong association with economic poverty and poor economic performance. This study uses a broad set of macro level indicators and makes the first attempt to measure energy poverty and its impact on economic growth of Pakistan over the period of 1990 to 2017. Our energy poverty indicator considers four main dimensions of energy poverty, namely, energy services, clean energy, energy governanc… Show more

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Cited by 24 publications
(8 citation statements)
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“…Furthermore, as indicated in Table 5 , empirical results display that the foreign direct investment coefficient at the 5% level is positive and statistically significant. This finding is also supported by Ullah et al ( 2021 ), who found that FDI inflows can encourage the establishment of large-scale renewable energy projects that have lower operating costs and higher shares of clean energy.…”
Section: Estimation Results and Discussionsupporting
confidence: 62%
“…Furthermore, as indicated in Table 5 , empirical results display that the foreign direct investment coefficient at the 5% level is positive and statistically significant. This finding is also supported by Ullah et al ( 2021 ), who found that FDI inflows can encourage the establishment of large-scale renewable energy projects that have lower operating costs and higher shares of clean energy.…”
Section: Estimation Results and Discussionsupporting
confidence: 62%
“…FDI inflows to developing countries bring investment to these capital-scarce economies. Capital inflows from abroad are essential for the provision of energy infrastructure in the host economies (Ullah et al 2021 ). Moreover, foreign firms bring energy-efficient appliances which can reduce energy intensity in the production processes (Elliott et al 2013 ; Pan et al 2020 ; Dong et al 2019 ).…”
Section: Empirical Results and Discussionmentioning
confidence: 99%
“…In line with Ullah et al (2021) [54], we adopted GDP per capita for economic development levels in provinces. Additionally, this analysis incorporated investment in forest areas and urbanization as controlled variables derived from prior research to mitigate potential biases due to omitted variables.…”
Section: Control Variablesmentioning
confidence: 99%