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Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective

by 1,†, 1,†, 1, 1 and 2,*
1
Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
2
College of Engineering, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work and should be considered co-first authors.
Sustainability 2020, 12(19), 8097; https://doi.org/10.3390/su12198097
Received: 2 September 2020 / Revised: 26 September 2020 / Accepted: 28 September 2020 / Published: 1 October 2020
(This article belongs to the Section Air, Climate Change and Sustainability)
Emission reduction strategies based on provinces are key for China to mitigate its carbon emission intensity (CEI). As such, it is valuable to analyze the driving mechanism of CEI from a provincial view, and to explore a coordinated emission mitigation mechanism. Based on spatial econometrics, this study conducts a spatial-temporal effect analysis on CEI, and constructs a Spatial Durbin Model on the Panel data (SDPM) of CEI and its eight influential factors: GDP, urbanization rate (URB), industrial structure (INS), energy structure (ENS), energy intensity (ENI), technological innovation (TEL), openness level (OPL), and foreign direct investment (FDI). The main findings are as follows: (1) overall, there is a significant and upward trend of the spatial autocorrelation of CEI on 30 provinces in China. (2) The spatial spillover effect of CEI is positive, with a coefficient of 0.083. (3) The direct effects of ENI, ENS and TEL are significantly positive in descending order, while INS and GDP are significantly negative. The indirect effects of URB and ENS are significantly positive, while GDP, ENI, OPL and FDI are significantly negative in descending order. Economic and energy-related emission reduction measures are still crucial to the achievement of CEI reduction targets for provinces in China. View Full-Text
Keywords: carbon emission intensity; spatial econometrics; panel data; spatial Durbin model; regional cooperation; China carbon emission intensity; spatial econometrics; panel data; spatial Durbin model; regional cooperation; China
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MDPI and ACS Style

Xue, L.-M.; Meng, S.; Wang, J.-X.; Liu, L.; Zheng, Z.-X. Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective. Sustainability 2020, 12, 8097. https://doi.org/10.3390/su12198097

AMA Style

Xue L-M, Meng S, Wang J-X, Liu L, Zheng Z-X. Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective. Sustainability. 2020; 12(19):8097. https://doi.org/10.3390/su12198097

Chicago/Turabian Style

Xue, Li-Ming, Shuo Meng, Jia-Xing Wang, Lei Liu, and Zhi-Xue Zheng. 2020. "Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective" Sustainability 12, no. 19: 8097. https://doi.org/10.3390/su12198097

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