Marginal effect of electricity generation on CO2 emissions: Disaggregated level evidence from China by KRLS method and high-frequency daily data

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dc.authoridMagazzino, Cosimo/0000-0002-3176-9838
dc.authoridKartal, Mustafa Tevfik/0000-0001-8038-8241
dc.contributor.authorKartal, Mustafa Tevfik
dc.contributor.authorMagazzino, Cosimo
dc.contributor.authorPata, Ugur Korkut
dc.date.accessioned2024-09-18T20:16:44Z
dc.date.available2024-09-18T20:16:44Z
dc.date.issued2024
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractThe 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 similar to 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.en_US
dc.identifier.doi10.1016/j.esr.2024.101382
dc.identifier.issn2211-467X
dc.identifier.issn2211-4688
dc.identifier.scopus2-s2.0-85190325260en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.esr.2024.101382
dc.identifier.urihttps://hdl.handle.net/20.500.12483/9717
dc.identifier.volume53en_US
dc.identifier.wosWOS:001231014500001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofEnergy Strategy Reviewsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectElectricity generation & CO2 emissionsen_US
dc.subjectDisaggregated level analysisen_US
dc.subjectDaily dataen_US
dc.subjectChinaen_US
dc.subjectKRLS methoden_US
dc.titleMarginal effect of electricity generation on CO2 emissions: Disaggregated level evidence from China by KRLS method and high-frequency daily dataen_US
dc.typeArticleen_US

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