Spatio-temporal Features of Industrial Carbon Efficiency and Its Influence Elements Analysis

Empirical Evidence from China

Authors

  • Xinjun Li

DOI:

https://doi.org/10.54097/fbem.v11i3.13193

Keywords:

Industry Carbon Emission Efficiency, Super-efficient SBM model, Spatio-temporal characteristics, Spatial Panel Durbin Model.

Abstract

The assessment of industrial carbon emission efficiency and the investigation of its influence elements are hot topics in environmental economics. Supported by SBM model, this paper uses the information of 30 provinces from 2005 to 2020 to study the spatial-temporal evolution of China's industrial carbon emission efficiency and its influencing factors. This paper believes that, in terms of direct effects, the energy structure, industrial structure, property rights structure, environmental control and foreign direct investment level will greatly influence the industrial carbon emission efficiency; with regard to indirect effects, the property rights structure, environmental control and foreign direct investment level significantly influence the industrial carbon emission efficiency.

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References

Kaya Y, Yokobori K. (1997). Environment, energy, and economy: Strategies for sustainability. United Nations University Press, Tokyo.

Lin L, Heng Z. (2021). Study on the relationship between the integration of “Two industries” and carbon emission efficiency. Economic Survey, 38(5): 71-79.

Yingqi X, Yu C, Jing W. (2022). Spatio-temporal evolution and influencing factors of carbon emission efficiency in low-carbon pilot cities in China. Journal pf Natural Resources, 37(5):1261-1276.

Jian L, Min W. (2022). Dual environmental regulation, FDI and green Total factor productivity: a case study of three urban agglomerations in the Yangtze River economic belt. East China Economic Management, 36(1):31-41.

Sanliang J, Caibao L. (2022). Externalities and heterogeneity of environmental regulation on carbon emission efficiency: an analysis based on the agglomeration synergy of producer services. East China Economic Management, 36(10):56-69

Li Y, Liang H. (2022). Impact of different types of capital-biased technological progress on carbon emission efficiency. Science and Technology research, 42(14):211-218

Guangming L, Weijie Z. (2017). Study on industrial carbon emissions and emission reduction mechanism under crbon trading in China. Chinese Journal of Population Resources and Environment, 27(10): 141-148.

Hui W, Yijie B, Shuqiao W. (2016). Dynamic Evolution and spatial spillover of export trade, industrial carbon emission efficiency. Journal of Quantitative & Technical Economics, 12(1):3-19.

Chenyao Qu. (2017). Impact of industrial agglomeration on carbon emission efficiency of China’s manufacturing industry and its regional differences. Soft Science, 6(1):34-38.

Tone K. (2003). Dealing with undesirable outputs in DEA:A slacks-based measure(SBM) approach. GRIPS Research Report Series 1, 0005.

LeSage, J., and K. Pace. (2009) Introduction to Spatial Econometrics. CRC Press, Boca Raton.

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Published

26-10-2023

Issue

Section

Articles

How to Cite

Li, X. (2023). Spatio-temporal Features of Industrial Carbon Efficiency and Its Influence Elements Analysis: Empirical Evidence from China. Frontiers in Business, Economics and Management, 11(3), 85-90. https://doi.org/10.54097/fbem.v11i3.13193