Abstract
The study examines the asymmetric effect of electricity consumption on carbon dioxide (CO2) emissions by analyzing end-user groups. In this context, the study focuses on the USA, which is the largest economy. The study includes the most available monthly data from January 1973 to November 2021, performs nonlinear quantile approaches as Granger causality-in-quantiles, nonparametric causality-in-quantiles, and quantile-on-quantile regression (QQR). Besides, quantile regression (QR) approach is used for robustness checks. The empirical results show that (i) correlation relationship between the electricity consumption and CO2 emissions changes according to the terms; (ii) there are generally causality effects in quantiles excluding some lower (0.05, 0.25), middle (0.70, 0.75), and high (0.95) quantiles, while the results for end-user groups vary; (iii) similarly, there is nonparametric causality from the end-user electricity consumption indicators to the CO2 emissions for the mean (return) and the variance (volatility) in most of the quantiles excluding some; (iv) the effects of the electricity consumption indicators on the CO2 emissions are higher in lower quantiles; (v) the QR results show the robustness of the QQR results. Overall, the effects of the electricity consumption indicators on the CO2 emissions are asymmetric and change according to the terms, quantiles, mean, variance, and end-user groups. Furthermore, policy implications are discussed.
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Data availability
The data that support the findings of this study are available in the US Energy Information Administration (EIA) at https://www.eia.gov/totalenergy/data/monthly.
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Mustafa Tevfik Kartal: the design of the study, conceptualization; methodology; data collection; econometric analysis; writing—original draft; writing—review and editing; Uzair Ali: writing—review and editing; Zhanar Nurgazina: writing—review and editing.
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Kartal, M.T., Ali, U. & Nurgazina, Z. Asymmetric effect of electricity consumption on CO2 emissions in the USA: analysis of end-user electricity consumption by nonlinear quantile approaches. Environ Sci Pollut Res 29, 83824–83838 (2022). https://doi.org/10.1007/s11356-022-21715-8
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DOI: https://doi.org/10.1007/s11356-022-21715-8