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How government regulation impacts on energy and CO2 emissions performance in China's mining industry

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  • Ma, Ding
  • Fei, Rilong
  • Yu, Yongsheng

Abstract

Mining industry, well known as the supply foundation of the nation's entire industrial production, is critical in China's endeavor in resource conservation and emission reduction. The spatial and temporal evolution characteristics of the unified inputs-outputs efficiency are firstly studied based on non-radial directional distance function and Malmquist index decomposition. On this basis, panel regression models are built to identify drivers of the measured efficiency evolution in China's mining sector. Our empirical results reveal that: (i) unified inputs-outputs efficiency in China's mining sector exhibits an essentially descending trend on the whole and the regional disparity is not as pronounced as other industries; (ii) state ownership stake exerts a negative effect, whereas private ownership stake exerts a positive influence on the unified input-output efficiency; (iii) government regulation did not impel mining industry toward a more efficient mode of operating but hindered efficiency enhancement, and this is especially distinct in private-owned enterprises; (iv) regional economic development and R&D could be conducive to the improvement of unified input-output efficiency while energy price did not effectively motivate input conservation. The results offer some clues for policy-makers of the mining industry, for improving its sustainable and efficient industrial operating.

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  • Ma, Ding & Fei, Rilong & Yu, Yongsheng, 2019. "How government regulation impacts on energy and CO2 emissions performance in China's mining industry," Resources Policy, Elsevier, vol. 62(C), pages 651-663.
    • Handle: RePEc:eee:jrpoli:v:62:y:2019:i:c:p:651-663
    DOI: 10.1016/j.resourpol.2018.11.013
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    as
    1. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Shao, Shuai & Liu, Jianghua & Geng, Yong & Miao, Zhuang & Yang, Yingchun, 2016. "Uncovering driving factors of carbon emissions from China’s mining sector," Applied Energy, Elsevier, vol. 166(C), pages 220-238.
    3. Rubashkina, Yana & Galeotti, Marzio & Verdolini, Elena, 2015. "Environmental regulation and competitiveness: Empirical evidence on the Porter Hypothesis from European manufacturing sectors," Energy Policy, Elsevier, vol. 83(C), pages 288-300.
    4. Ramli, Noor Asiah & Munisamy, Susila, 2015. "Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure," Economic Modelling, Elsevier, vol. 47(C), pages 219-227.
    5. Duan, Na & Guo, Jun-Peng & Xie, Bai-Chen, 2016. "Is there a difference between the energy and CO2 emission performance for China’s thermal power industry? A bootstrapped directional distance function approach," Applied Energy, Elsevier, vol. 162(C), pages 1552-1563.
    6. M. Diaz & Rosario Sanchez, 2008. "Firm size and productivity in Spain: a stochastic frontier analysis," Small Business Economics, Springer, vol. 30(3), pages 315-323, March.
    7. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    8. Hering, Laura & Poncet, Sandra, 2014. "Environmental policy and exports: Evidence from Chinese cities," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 296-318.
    9. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    10. Sun, Sizhong & Anwar, Sajid, 2015. "R&D status and the performance of domestic firms in China's coal mining industry," Energy Policy, Elsevier, vol. 79(C), pages 99-103.
    11. Boycko, Maxim & Shleifer, Andrei & Vishny, Robert W, 1996. "A Theory of Privatisation," Economic Journal, Royal Economic Society, vol. 106(435), pages 309-319, March.
    12. Ma, Yiqun, 2015. "Uncertainty and investment: Evidence from the Australian mining industry," Resources Policy, Elsevier, vol. 46(P2), pages 191-201.
    13. Wang, Miao & Feng, Chao, 2017. "Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications," Resources Policy, Elsevier, vol. 53(C), pages 77-87.
    14. Li, Mingquan & Wang, Qi, 2014. "International environmental efficiency differences and their determinants," Energy, Elsevier, vol. 78(C), pages 411-420.
    15. Gray, Wayne B, 1987. "The Cost of Regulation: OSHA, EPA and the Productivity Slowdown," American Economic Review, American Economic Association, vol. 77(5), pages 998-1006, December.
    16. Fei, Rilong & Lin, Boqiang, 2017. "The integrated efficiency of inputs–outputs and energy – CO2 emissions performance of China's agricultural sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 668-676.
    17. Fan, Songmei & Yan, Jingjing & Sha, Jinghua, 2017. "Innovation and economic growth in the mining industry: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 54(C), pages 25-42.
    18. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    19. Li, Jianglong & Lin, Boqiang, 2017. "Ecological total-factor energy efficiency of China's heavy and light industries: Which performs better?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 83-94.
    20. Song, Zongyun & Niu, Dongxiao & Xiao, Xinli, 2017. "Focus on the current competitiveness of coal industry in China: Has the depression time gone?," Resources Policy, Elsevier, vol. 51(C), pages 172-182.
    21. Fisher-Vanden, Karen & Jefferson, Gary H. & Liu, Hongmei & Tao, Quan, 2004. "What is driving China's decline in energy intensity?," Resource and Energy Economics, Elsevier, vol. 26(1), pages 77-97, March.
    22. Yin, Jianhua & Zheng, Mingzheng & Chen, Jian, 2015. "The effects of environmental regulation and technical progress on CO2 Kuznets curve: An evidence from China," Energy Policy, Elsevier, vol. 77(C), pages 97-108.
    23. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    24. Moon, Hana & Min, Daiki, 2017. "Assessing energy efficiency and the related policy implications for energy-intensive firms in Korea: DEA approach," Energy, Elsevier, vol. 133(C), pages 23-34.
    25. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    26. Xu, Hangtian & Nakajima, Kentaro, 2016. "Did China's coal mine regulation positively affect economic growth?," Resources Policy, Elsevier, vol. 50(C), pages 160-168.
    27. Peng, Lihong & Zhang, Yiting & Wang, Yejun & Zeng, Xiaoling & Peng, Najun & Yu, Ang, 2015. "Energy efficiency and influencing factor analysis in the overall Chinese textile industry," Energy, Elsevier, vol. 93(P1), pages 1222-1229.
    28. Shen, Lixin & Muduli, Kamalakanta & Barve, Akhilesh, 2015. "Developing a sustainable development framework in the context of mining industries: AHP approach," Resources Policy, Elsevier, vol. 46(P1), pages 15-26.
    29. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    30. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    31. Sanz-Díaz, María Teresa & Velasco-Morente, Francisco & Yñiguez, Rocío & Díaz-Calleja, Emilio, 2017. "An analysis of Spain's global and environmental efficiency from a European Union perspective," Energy Policy, Elsevier, vol. 104(C), pages 183-193.
    32. Wang, H. & Zhou, P. & Zhou, D.Q., 2013. "Scenario-based energy efficiency and productivity in China: A non-radial directional distance function analysis," Energy Economics, Elsevier, vol. 40(C), pages 795-803.
    33. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    34. 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.
    35. Chen, Weidong & Geng, Wenxin, 2017. "Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input," Energy, Elsevier, vol. 120(C), pages 283-292.
    36. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    37. Song, Malin & Song, Yaqing & An, Qingxian & Yu, Huayin, 2013. "Review of environmental efficiency and its influencing factors in China: 1998–2009," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 8-14.
    38. Fare, Rolf & Grosskopf, Shawna & Logan, James, 1983. "The relative efficiency of Illinois electric utilities," Resources and Energy, Elsevier, vol. 5(4), pages 349-367, December.
    39. Guo, Xiao-Dan & Zhu, Lei & Fan, Ying & Xie, Bai-Chen, 2011. "Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA," Energy Policy, Elsevier, vol. 39(5), pages 2352-2360, May.
    40. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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