Abstract

The effect of energy use on carbon dioxide (CO2) emissions has been frequently studied in the literature. These studies have mainly concluded that countries should decline (increase) the use of fossil fuel (clean) energy. However, the literature suffers from a significant shortcoming as it does not focus on the marginal effect of a 1 % increase for each energy generation source on sectoral CO2 emissions. Therefore, a detailed analysis is conducted in this study to examine the relationship between electricity generation (EG) and CO2 emissions at a disaggregated level. The focus is on China, the world's leading country in terms of CO2 emissions and energy use. Thus, the study considers source-based EG and sector-based CO2 emissions, uses high-frequency daily data between January 1, 2019, and December 31, 2022, and applies the kernel-based regularized least squares (KRLS) method. The outcomes show that (i) the effects of EG sources on sectoral CO2 emissions follow a nonlinear structure, suggesting that the marginal effect varies by sector, EG sources, and estimation models (either incremental or degressive). Therefore, there are certain externalities among alternative EG sources for the effects of CO2 emissions in the sectors; (ii) the statistically significant effects of EG sources on CO2 emissions vary by sector and constructed models, showing that some EG sources are much more important for CO2 emissions in some sectors. For this reason, not all EG sources have the same importance for sectoral CO2 emissions; (iii) the KRLS method has a higher estimation ability of CO2 emissions, reaching ∼99.8 %, which provides novel outcomes and allows researchers to argue various policy options based on the obtained results. The study thus highlights varying marginal impacts of EG sources on sectoral CO2 emissions. The changing marginal influence is a crucial point that should be considered by Chinese policymakers when formulating energy-related environmental policies.

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