Spatial Distribution and Regional Difference of Carbon Emissions Eciency of Industrial Energy in China Fang Liu Jiangsu University of Technology Lu Tang Jishou University Kaicheng Liao (
[email protected] ) Tongji University Lijuan Ruan Changzhou University Pingsheng Liu Zhongshan Torch Polytechnic Research Article Keywords: Carbon emissions eciency of industrial energy, Regional difference, Spatial distribution, SBM-DEA model Posted Date: July 8th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-684325/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Spatial distribution and regional difference of carbon emissions efficiency of industrial energy in China Fang Liu1, Lu Tang2, Kaicheng Liao3,*, Lijuan Ruan4, Pingsheng Liu5 1 Business School, Jiangsu University of Technology, Changzhou 213001, China 2 Business School, Jishou University, Jishou 416000, China 3 School of Economics and Management, Tongji University, Shanghai 200092, China 4 Shiliang Law School, Changzhou University, Changzhou 213164, China 5 School of Finance and Commerce, Zhongshan Torch Polytechnic, Zhongshan 528436, China * Correspondence: Kaicheng Liao,
[email protected] Spatial distribution and regional difference of carbon emissions efficiency of industrial energy in China Abstract The three-stage super-efficiency slack-based measure and data envelopment analysis (SBM-DEA) model with undesirable outputs is used to calculate carbon emissions efficiency of industrial energy (CEEIE) of 30 provinces in China from 2000 to 2017. Then ArcGIS software is used to illustrate the spatial distribution of CEEIE, and Dagum Gini ratio is calculated to decompose the regional difference. The results show that the spatial distribution of CEEIE changes from disorder to order and provinces characterized with high or low CEEIE cluster in space over time.