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

Li-Ming Xue, Shuo Meng, Jia-Xing Wang, Lei Liu and Zhi-Xue Zheng
Additional contact information
Li-Ming Xue: Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
Shuo Meng: Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
Jia-Xing Wang: Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
Lei Liu: Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
Zhi-Xue Zheng: College of Engineering, Peking University, Beijing 100871, China

Sustainability, 2020, vol. 12, issue 19, 1-26

Abstract: 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.

Keywords: carbon emission intensity; spatial econometrics; panel data; spatial Durbin model; regional cooperation; China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/19/8097/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/19/8097/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:19:p:8097-:d:422373

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().