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Measuring capacity utilization under the constraints of energy consumption and CO2 emissions using meta-frontier DEA: A case of China's non-ferrous metal industries

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  • Wang, Miao
  • Feng, Chao

Abstract

Currently, China's non-ferrous metal industry (NMI) still has the problem of overcapacity, measuring its capacity utilization (CU) and revealing its determinants is an important way to resolve the overcapacity problem of China's NMI. Using the panel data of China's 29 NMIs, this paper constructs a meta-frontier data envelopment analysis (DEA) to measure CU by taking into account the energy consumption and CO2 emissions constraints, and decompose the CU into four parts: technical efficiency, technology gap, scale efficiency, and equipment utilization. The main findings indicate that during the period of 2004–2017, the CU of China's NMI is generally low. Non-ferrous metal alloy manufacturing and rolling processing has the highest CU, while non-ferrous metals mining and dressing shows the lowest CU. From the dynamic perspective, mining and dressing experienced CU decrease, while other two sub-industries achieved CU increase. Technical inefficiency and technology gap enlargement are two main barriers of China's NMIs' CU. Besides, among 29 NMIs, there are only ten industries witnessed a CU improvement, while the remaining nineteen industries all experienced decrease of CU. CU and its determinants across China's 29 NMIs are quite different. Thus, the policies to improve CU should be made tailored to each industry's features.

Suggested Citation

  • Wang, Miao & Feng, Chao, 2023. "Measuring capacity utilization under the constraints of energy consumption and CO2 emissions using meta-frontier DEA: A case of China's non-ferrous metal industries," Resources Policy, Elsevier, vol. 80(C).
  • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722007218
    DOI: 10.1016/j.resourpol.2022.103278
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    as
    1. Zhu, Bangzhu & Xu, Chenxin & Wang, Ping & Zhang, Lin, 2022. "How does internal carbon pricing affect corporate environmental performance?," Journal of Business Research, Elsevier, vol. 145(C), pages 65-77.
    2. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    3. C. J. O'Donnell & W. E. Griffiths, 2006. "Estimating State-Contingent Production Frontiers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 249-266.
    4. Chiu, Yung-ho & Huang, Kuei-Ying & Chang, Tzu-Han & Lin, Tai-Yu, 2021. "Efficiency assessment of coal mine use and land restoration: Considering climate change and income differences," Resources Policy, Elsevier, vol. 73(C).
    5. 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.
    6. Yang, Qing & Hou, Xiaochao & Zhang, Lei, 2018. "Measurement of natural and cyclical excess capacity in China's coal industry," Energy Policy, Elsevier, vol. 118(C), pages 270-278.
    7. Tian, Ying & Feng, Chao, 2022. "The internal-structural effects of different types of environmental regulations on China's green total-factor productivity," Energy Economics, Elsevier, vol. 113(C).
    8. Ji, Yuhang & Lei, Yalin & Li, Li & Zhang, An & Wu, Sanmang & Li, Qun, 2021. "Evaluation of the implementation effects and the influencing factors of resource tax in China," Resources Policy, Elsevier, vol. 72(C).
    9. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    10. Yang, Jun & Hao, Yun & Feng, Chao, 2021. "A race between economic growth and carbon emissions: What play important roles towards global low-carbon development?," Energy Economics, Elsevier, vol. 100(C).
    11. Subhash C. Ray & John Walden & Lei Chen, 2018. "Economic Measures of Capacity Utilization: A Nonparametric Cost Function Analysis," Working papers 2018-02, University of Connecticut, Department of Economics.
    12. Lu, Juan & Li, He, 2022. "Can high-speed rail improve enterprise capacity utilization? A perspective of supply side and demand side," Transport Policy, Elsevier, vol. 115(C), pages 152-163.
    13. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    14. Yang, Guo-liang & Fukuyama, Hirofumi, 2018. "Measuring the Chinese regional production potential using a generalized capacity utilization indicator," Omega, Elsevier, vol. 76(C), pages 112-127.
    15. Wang, Miao & Feng, Chao, 2021. "Towards a decoupling between economic expansion and carbon dioxide emissions in resources sector: A case study of China’s 29 non-ferrous metal industries," Resources Policy, Elsevier, vol. 74(C).
    16. Berndt, Ernst R & Morrison, Catherine J, 1981. "Capacity Utilization Measures: Underlying Economic Theory and an Alternative Approach," American Economic Review, American Economic Association, vol. 71(2), pages 48-52, May.
    17. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    18. Yu, Ming-Miin & Chang, Yu-Chun & Chen, Li-Hsueh, 2016. "Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 186-198.
    19. Sahoo, Biresh K. & Tone, Kaoru, 2009. "Decomposing capacity utilization in data envelopment analysis: An application to banks in India," European Journal of Operational Research, Elsevier, vol. 195(2), pages 575-594, June.
    20. Li, Mengjie & Du, Weijian, 2022. "Opening the black box of capacity governance: Environmental regulation and capacity utilization of microcosmic firms in China," Economic Modelling, Elsevier, vol. 108(C).
    21. 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.
    22. Anwar M. Shaikh & Jamee K. Moudud, 2004. "Measuring Capacity Utilization in OECD Countries: A Cointegration Method," Economics Working Paper Archive wp_415, Levy Economics Institute.
    23. Fukuyama, Hirofumi & Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2021. "Measuring the capacity utilization of the 48 largest iron and steel enterprises in China," European Journal of Operational Research, Elsevier, vol. 288(2), pages 648-665.
    24. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    25. Wang, Yongpei & Yan, Weilong & Komonpipat, Supak, 2019. "How does the capacity utilization of thermal power generation affect pollutant emissions? Evidence from the panel data of China's provinces," Energy Policy, Elsevier, vol. 132(C), pages 440-451.
    26. Wang, Miao & Feng, Chao, 2020. "The impacts of technological gap and scale economy on the low-carbon development of China's industries: An extended decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    27. Zhuo-wan Liu & Tomas Balezentis & Yao-yao Song & Guo-liang Yang, 2019. "Estimating Capacity Utilization of Chinese State Farms," Sustainability, MDPI, vol. 11(18), pages 1-29, September.
    28. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2019. "Estimating capacity utilization of Chinese manufacturing industries," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 94-110.
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