Evaluation and Dynamic Evolution of the Total Factor Environmental Efficiency in China’s Mining Industry

Xiangqian Wang, Shudong Wang and Yongqiu Xia
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Xiangqian Wang: College of Economy and Management, Anhui University of Science & Technology, Huainan 232001, China
Shudong Wang: College of Economy and Management, Anhui University of Science & Technology, Huainan 232001, China
Yongqiu Xia: College of Economy and Management, Anhui University of Science & Technology, Huainan 232001, China

Energies, 2022, vol. 15, issue 3, 1-19

Abstract: The mining industry plays an extremely important strategic role in China’s economic and social development. In the new era of pursuing circular/green/efficient development, the evaluation of the total factor environmental efficiency (TFEE) of China’s mining industry is essential for alleviating resource waste and environmental pollution. The Epsilon-Based Measure (EBM) model effectively solves the shortcomings of radial and non-radial DEA models. In addition, the Malmquist–Luenberger (ML) index can measure the dynamic change of efficiency value. Combining the EBM model and the ML productivity index, this paper evaluates the TFEE from the static and dynamic perspective in China’s 31 provincial mining industries over the period 2007–2016. The Theil index is employed to reveal the root of the overall provincial TFEE gap (OGTFEE) in China’s mining industry. The results show that the average total factor static environmental efficiency (TFSEE) of China’s provincial mining industry exhibits a low score of 0.6589 and with significant spatio-temporal differences. The provincial TFEE gap within four major areas (WGTFEE), especially that in east and west areas, is the main cause of the OGTFEE in China’s mining industry. Technical change contributes more to the TFEE decline in China’s mining industry. There are differences in improving the TFEE among China’s 31 provincial mining industries, and corresponding countermeasures can be formulated accordingly. This study provides theoretical and practical basis for the clean and green development of China’s mining industry.

Keywords: mining industry; environmental efficiency; spatio-temporal differences; EBM model; ML productivity index (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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