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Industrial CO 2 Emissions Efficiency and its Determinants in China: Analyzing Differences Across Regions and Industry Sectors
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Industrial CO2 Emissions Efficiency and its Determinants in China: Analyzing Differences Across Regions and Industry Sectors
Chen Shen1, 2, Rui Feng3, Binbin Yu1, Zhongju Liao1
1Zhejiang Sci-Tech University, School of Economics and Management, 310018, Zhejiang, China
2Zhejiang Sci-Tech University, Zhejiang Ecological Civilization Research Center, 310018, Zhejiang, China
3Guangzhou University, School of Economics and Statistics, 510006, Guangzhou, China
Final revision date: 2017-08-30
Online publication date: 2018-02-27
Pol. J. Environ. Stud. 2018;27(3):1239–1254
industrial CO2 emissions efficiency
modified Super-SBM model with undesirable outputs
Dagum Gini coefficient and subgroup decomposition method
This paper utilizes industrial CO2 emissions efficiency as a measure of the low-carbon transformation index and used industrial provincial panel data during 1997-2014 and industrial panel data during 2000- 14 based on the modified Super-SBM model with undesirable outputs that measure carbon efficiency levels of different provinces and industrial sectors in China. Differences among sectors and provinces were calculated using the Dagum Gene coefficient and the subgroup decomposition method, and the determinants of carbon efficiency were explored by regression analysis. It turns out that industrial CO2 emissions efficiency in China is generally low, and it has been steadily improving since 2003. Industrial carbon efficiency shows the unbalanced characteristics (high in eastern areas, low in western areas) and the value of the western regions was overtaken by the central region during the period of the 12th Five-Year Plan. From the perspective of industrial sectors, industrial CO2 emissions efficiency of lightly polluted industries is significantly higher than that of moderately and heavily polluted industries. In addition, the carbon efficiency of technology-intensive industries and clean production industries as part of industries with light pollution is at an optimal level, while that of some resource-intensive industries and traditional manufacturing industries is relatively low. Both the regional and industrial sectors’ Dagum Gini coefficients of industrial carbon efficiency exhibit the tendency of down first, and then up and stable on the whole. The regional disequilibrium problem mainly arises from the gap between the eastern and western regions, and the inter-industry gap is primarily manifested between heavily polluted and lightly polluted industries. The relationship between scale effect and industrial carbon efficiency presents a “U”-type curve. Ownership structure, technological innovation, government environment, and openness degree can all have a positive effect on industrial carbon efficiency, while endowment structure and energy consumption structure exert markedly negative effects. However, effects of these factors differ among different areas and different sectors.
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