Nuclear energy, economic growth and CO2 emissions in Pakistan: Evidence from extended STRIPAT model
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Pakistan is a developing country whose maximum amount of mixed energy is provided by electricity, oil, coal, and gas. The study objective is to analyze the six major social factors to describe the significance of nuclear energy and CO2 emissions at the decisive point coming from income, trade, energy, and urbanization. This study has tried to analyze the impact of different factors (i.e., fossil energy, GDP per capita, overall population, urban population, and merchandise trade) on Pakistan’s CO2 emissions using the extended STRIPAT model from 1986 to 2021. Ridge regression has been applied to analyze the parameters due to the multicollinearity problem in the data. The results show that (i) all the factors show significant results on carbon emissions; (ii) population and energy factors are the huge contributors to raising CO2 emissions by 0.15% and 0.16%; however, merchandise and GDP per capita are the least contributing factors by 0.12% and 0.13% due to import/export and income level in Pakistan, and (iii) nuclear energy and substitute overall show a prominent and growing impact on CO2 emissions by 0.16% and 0.15% in Pakistan. Finally, empirical results have wider applications for energy-saving, energy substitution, capital investment, and CO2 emissions mitigation policies in developing countries. Moreover, by investigating renewable energy technologies and renewable energy sources, insights are provided on future CO2 emissions reduction.
Abstract
Pakistan is a developing country whose maximum amount of mixed energy is provided by electricity, oil, coal, and gas. The study objective is to analyze the six major social factors to describe the significance of nuclear energy and CO2 emissions at the decisive point coming from income, trade, energy, and urbanization. This study has tried to analyze the impact of different factors (i.e., fossil energy, GDP per capita, overall population, urban population, and merchandise trade) on Pakistan’s CO2 emissions using the extended STRIPAT model from 1986 to 2021. Ridge regression has been applied to analyze the parameters due to the multicollinearity problem in the data. The results show that (i) all the factors show significant results on carbon emissions; (ii) population and energy factors are the huge contributors to raising CO2 emissions by 0.15% and 0.16%; however, merchandise and GDP per capita are the least contributing factors by 0.12% and 0.13% due to import/export and income level in Pakistan, and (iii) nuclear energy and substitute overall show a prominent and growing impact on CO2 emissions by 0.16% and 0.15% in Pakistan. Finally, empirical results have wider applications for energy-saving, energy substitution, capital investment, and CO2 emissions mitigation policies in developing countries. Moreover, by investigating renewable energy technologies and renewable energy sources, insights are provided on future CO2 emissions reduction.
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