A Quantile Regression Analysis of the Impact of Electricity Production Sources on CO2 Emission in South Asian Countries
DOI:
https://doi.org/10.13052/spee1048-5236.4223Keywords:
Climate change, CO2 emissions, Electricity production sources, Energy consumption, Quantile RegressionAbstract
This study wants to fill a gap in the empirical literature by looking at how the sources of electricity affect CO2 emissions in South Asian countries. Because of the consistent production levels and economic growth in South Asian countries, energy generation is becoming a key issue. The data, which covers from 1972 to 2015, is subjected to quantile regression (QR). The quantile regression coefficients’ findings are statistically significant at a 1% level of significance. According to the regression results, all energy generation sources and associated variables have a positive impact on CO2 emissions. Coal-fired power plants have a bigger impact on the environment than other types of pollution. On the other hand, renewable energy sources have the minimum impact on environmental degradation. Possible alternatives for reducing carbon dioxide emissions instead of coal, oil, and gas-based energy production sources have been presented. The policy implications also suggest that environmental policy should be improved by applying renewable energy, wind energy, hydroelectric sources, and nuclear energy. The link between economic growth and energy concentration needs to be looked into more with the help of more economic indicators and the parameters of electricity-generating sources.
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