Spatio-Temporal Evolution and Drivers of Carbon Emission Efficiency in China’s Iron and Steel Industry

Rongbang Xu, Fujie Yang, Sanmang Wu () and Qinwen Xue
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Rongbang Xu: School of Economics and Management, China University of Geosciences, Beijing 100083, China
Fujie Yang: School of Economics and Management, China University of Geosciences, Beijing 100083, China
Sanmang Wu: School of Economics and Management, China University of Geosciences, Beijing 100083, China
Qinwen Xue: School of Economics and Management, China University of Geosciences, Beijing 100083, China

Sustainability, 2024, vol. 16, issue 12, 1-22

Abstract: Improving the carbon emission efficiency (CEE) of the iron and steel industry (ISI) is crucial for China to achieve the goal of carbon peak and carbon neutrality. This study employed the undesirable SBM and Dagum Gini coefficient to measure the ISI’s CEE and analyzed the spatial heterogeneity among three regions of China. This study also used the Tobit model to clarify the influencing factors. The conclusions show that (1) the CEE in eastern provinces is the highest, the central ones rank second, while the western ones rank the worst; the promoting effect of Technical Change is greater than that of Efficiency Change. (2) ISI’s CEE shows a positive spatial correlation and an apparent spatial heterogeneity. The CEE gap between the regions contributes most to the CEE difference among provinces. The regional CEE gap within the western region is the largest, with a maximum difference of 0.520 in the Dagum Gini coefficient. Furthermore, the total CEE gap shows a narrowing trend from 2009 to 2020, with the Dagum Gini coefficient decreasing from 0.414 in 2009 to 0.357 in 2020. (3) Industrial structure, enterprise scale, foreign direct investment, and technology level positively correlate with ISI’s CEE; the marginal impacts are 0.6711, 0.1203, 0.0572, and 3.5191, respectively. While energy intensity, environmental regulation, and product structure negatively correlate with it, the marginal impacts are 0.0178, 1.4673, and 0.2452, respectively.

Keywords: carbon emission efficiency; iron and steel industry; Dagum Gini coefficient; Tobit model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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