The moderating role of green energy and energy-innovation in environmental kuznets: Insights from quantile-quantile analysis

Background. The recent environmental challenges in Africa emanated from global warming, human activity, limited access to electricity, and over-exploitation of natural resources, have contributed to the growth of carbon dioxide (CO2) emissions in the region. Objective. This paper empirically investigates the moderating role of green energy consumption and energy innovation in the environmental Kuznets' curve for the Sub-Saharan African (SSA) region using data spanning from 1980 to 2018. Methods. A sample of 45 SSA countries for the period between 1980-2018 was studied. To solve for potential heteroscedasticity and endogeneity issues, we performed 2sls and panel quantile regression to give inference at various quantiles. Discussion. Empirical results confirm that green energy, energy innovation and natural resource abundance mitigate pollution in the SSA region. Besides, a threshold effect of energy innovation is estimated, which indicates the amount of energy innovation that SSA would require to reduce environment degradation. Our threshold model found that atleast 54 per cent of population need access to energy innovation before the region could be safe from environmental degradation. Conclusions. We conclude that investment in green energy, energy innovation, and conservation of natural resources will help to mitigate environmental degradation in SSA in the long run. Policies should be targeted towards encouraging the consumption of green energy, and more investment in energy innovation beyond the estimated threshold will save the region from pollution and its implications. Contribution: This study has contributed to the existing studies in different ways. This is the first study to explore the impact of green energy and energy innovation in SSA. We contribute to this line of research by implementing quantile techniques to examine the role of green energy and energy innovation in the environmental Kuznets' hypothesis. In addition, our threshold estimation provides practical implications for policy applications.