Abstract
In response to the climate change problem, ensuring a transformation to green economies is highly critical. Therefore, countries have been trying to make their economies decarbonized by taking various measures. Accordingly, this study examines the USA case by using carbon dioxide emissions (load capacity factor) as the main (robustness) environmental proxy, considers energy-related research and development (R&D) investment types as main explanatory variables, controls income and energy utilization sub-types, and performs a novel kernel-based least squares (KRLS) model on data from 1974 to 2022 to apply a marginal effect analysis. The results show that (i) R&D investment sub-types have an insignificant effect on carbon dioxide (CO2) emissions; (ii) income structure does not contribute in greening economy; (iii) among energy utilization sub-types, only renewable energy has a decreasing effect on CO2 emissions, whereas nuclear and fossil energy sub-types have a reverse ones; (iv) the effects of the factors on CO2 emissions differentiate across percentiles and estimation models; (v) the robustness of the empirical results are verified based on alternative indicator; (vi) the KRLS model has a high estimation capability around 99.7%. Hence, the empirical results reveal the critical role of renewable energy use, while the current R&D investment structure, energy utilization, and income are not supportive of a green economy in the USA because these do not provide a decrease in CO2 emissions.
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