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Research on the efficiency of the mining industry in China from the perspective of time and space

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  • Chen, Jiabin
  • Wen, Shaobo
  • Liu, Yuchen

Abstract

China's mining industry must satisfy the domestic demand and shoulder the responsibility of maintaining the integrity of the international industrial chain. However, its sustainable development is tightly restricted by limited resources and the environment. To enhance the competitiveness of China's mining industry and its ability to withstand risk, measures should be taken to improve the production efficiency. This paper studies the temporal and spatial variation in the efficiency of China's mining industry and the spatial correlation in regional efficiency. We innovatively adopt a super-SBM (slack-based measure) model with undesirable outputs and the Malmquist index to calculate the efficiency in 31 provinces between 2007 and 2016; then, we apply Moran's index to investigate the spatial autocorrelation in the efficiency of the mining industry. The results show that China's mining industry is efficient and shows a trend of technological retrogression. The common factor that characterizes provinces with large fluctuations in efficiency is excessive undesirable output (discharge of pollutants). Globally, there is no spatial correlation in regional efficiency. From a local perspective, Shanxi, Hubei, Sichuan, and Guizhou present an L-H cluster that forms a regional mining center, Chongqing. For policy, the results imply that cross-regional cooperation and the exchange of technology and management should be strengthened so that high-efficiency provinces can drive improvements among low-efficiency provinces. In the meantime, reducing pollutant discharge and developing technological innovation in line with green mining are common methods for preventing efficiency degradation.

Suggested Citation

  • Chen, Jiabin & Wen, Shaobo & Liu, Yuchen, 2022. "Research on the efficiency of the mining industry in China from the perspective of time and space," Resources Policy, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:jrpoli:v:75:y:2022:i:c:s0301420721004839
    DOI: 10.1016/j.resourpol.2021.102475
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    as
    1. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    2. Sequeira, Tiago & Morão, Hugo, 2020. "Growth accounting and regressions: New approach and results," International Economics, Elsevier, vol. 162(C), pages 67-79.
    3. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    4. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    5. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    6. Giacalone, Massimiliano & Nissi, Eugenia & Cusatelli, Carlo, 2020. "Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation," Energy Economics, Elsevier, vol. 33(2), pages 292-303, March.
    9. Zhou, Yan & Xing, Xinpeng & Fang, Kuangnan & Liang, Dapeng & Xu, Chunlin, 2013. "Environmental efficiency analysis of power industry in China based on an entropy SBM model," Energy Policy, Elsevier, vol. 57(C), pages 68-75.
    10. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    11. Zhang, Ning & Choi, Yongrok, 2013. "A comparative study of dynamic changes in CO2 emission performance of fossil fuel power plants in China and Korea," Energy Policy, Elsevier, vol. 62(C), pages 324-332.
    12. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    13. Tao, Xueping & Wang, Ping & Zhu, Bangzhu, 2016. "Provincial green economic efficiency of China: A non-separable input–output SBM approach," Applied Energy, Elsevier, vol. 171(C), pages 58-66.
    14. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    15. Li, Aijun & Zhang, Aizhen & Huang, Huijie & Yao, Xin, 2018. "Measuring unified efficiency of fossil fuel power plants across provinces in China: An analysis based on non-radial directional distance functions," Energy, Elsevier, vol. 152(C), pages 549-561.
    16. De Bartolo, Gilbert & Holzman, Franklyn D., 1985. "The effects of aggregation on the difference between Laspeyres and Paasche indices," Journal of Comparative Economics, Elsevier, vol. 9(1), pages 71-79, March.
    17. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    18. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    19. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    20. Zhu, Xuehong & Chen, Ying & Feng, Chao, 2018. "Green total factor productivity of China's mining and quarrying industry: A global data envelopment analysis," Resources Policy, Elsevier, vol. 57(C), pages 1-9.
    21. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    22. Yao, Xin & Zhou, Hongchen & Zhang, Aizhen & Li, Aijun, 2015. "Regional energy efficiency, carbon emission performance and technology gaps in China: A meta-frontier non-radial directional distance function analysis," Energy Policy, Elsevier, vol. 84(C), pages 142-154.
    23. Xiaoli, Zhao & Rui, Yang & Qian, Ma, 2014. "China's total factor energy efficiency of provincial industrial sectors," Energy, Elsevier, vol. 65(C), pages 52-61.
    24. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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