IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v78y2019icp109-128.html
   My bibliography  Save this article

Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness

Author

Listed:
  • Wang, Delu
  • Wan, Kaidi
  • Song, Xuefeng
  • Liu, Yun

Abstract

Developing a de-capacity scheme that is economical, fair, and efficient, has become a key problem affecting the smooth achievement of coal de-capacity targets. It is also an important policy issue with regard to the overall implementation of China's supply-side structural reforms. In this study, we use the production function method as well as the panel variable coefficient model to calculate the 25 provinces' boundary production functions for the coal industry, which leads to the estimation of the coal capacity and capacity utilization rate of each province. Taking into account the labor resettlement cost and disposal cost of fixed assets, a total cost function of coal de-capacity is established. The growth rate function of total factor productivity (TFP) in the coal industry is constructed by the Solow residual value method. An allocation model of coal de-capacity is then proposed, based on multi-objective nonlinear optimization with constraint conditions on the total reduction amount and minimum output of coal in each region. Finally, using the relevant data of China's 25 coal-producing provinces in 1990–2015, the allocation of coal de-capacity is obtained under the goal of minimizing the total cost and maximizing the TFP growth rate. The results show that the capacity utilization rate of China's coal industry is much lower than the lower limit of the reasonable utilization ratio, while TFP shows negative growth over a long period. The comparative analytical results indicate that in terms of total cost, the optimal allocation scheme is 44.5335 billion yuan lower than the government allocation scheme. The disposal cost of fixed assets and labor resettlement costs decrease by 29.2749 billion yuan and 15.2586 billion yuan respectively. In terms of TFP growth, the optimal allocation scheme has a 1.54% higher TFP growth rate compared with the government allocation scheme. In terms of fairness, the Gini coefficients of the optimal scheme calculated by various indexes are all smaller than 0.3, placing the scheme within the category of considerable or absolute fairness. In addition, we calculate the optimal allocation ratio of coal de-capacity in the situation where cost preference and quality preference of central government are considered, to verify the intrinsic consistency of the model. In brief, the optimal allocation scheme proposed in this study effectively realizes the integration of economy, efficiency, and fairness.

Suggested Citation

  • Wang, Delu & Wan, Kaidi & Song, Xuefeng & Liu, Yun, 2019. "Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness," Energy Economics, Elsevier, vol. 78(C), pages 109-128.
    • Handle: RePEc:eee:eneeco:v:78:y:2019:i:c:p:109-128
    DOI: 10.1016/j.eneco.2018.11.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988318304444
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2018.11.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Huiming & Zheng, Yu & Ozturk, U. Aytun & Li, Shanjun, 2016. "The impact of subsidies on overcapacity: A comparison of wind and solar energy companies in China," Energy, Elsevier, vol. 94(C), pages 821-827.
    2. Yuan, Jiahai & Li, Peng & Wang, Yang & Liu, Qian & Shen, Xinyi & Zhang, Kai & Dong, Liansai, 2016. "Coal power overcapacity and investment bubble in China during 2015–2020," Energy Policy, Elsevier, vol. 97(C), pages 136-144.
    3. 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.
    4. Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018. "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, vol. 70(C), pages 244-257.
    5. Zhang, Xiaohan & Winchester, Niven & Zhang, Xiliang, 2017. "The future of coal in China," Energy Policy, Elsevier, vol. 110(C), pages 644-652.
    6. Shen, Guangjun & Chen, Binkai, 2017. "Zombie firms and over-capacity in Chinese manufacturing," China Economic Review, Elsevier, vol. 44(C), pages 327-342.
    7. Bergerson, Joule & Lave, Lester, 2007. "The long-term life cycle private and external costs of high coal usage in the US," Energy Policy, Elsevier, vol. 35(12), pages 6225-6234, December.
    8. Wang, Delu & Wan, Kaidi & Song, Xuefeng, 2018. "Quota allocation of coal overcapacity reduction among provinces in China," Energy Policy, Elsevier, vol. 116(C), pages 170-181.
    9. Kavouridis, K. & Koukouzas, N., 2008. "Coal and sustainable energy supply challenges and barriers," Energy Policy, Elsevier, vol. 36(2), pages 693-703, February.
    10. 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.
    11. Ruixue Jia & Huihua Nie, 2017. "Decentralization, Collusion, and Coal Mine Deaths," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 105-118, March.
    12. Zhang, Yanfang & Zhang, Ming & Liu, Yue & Nie, Rui, 2017. "Enterprise investment, local government intervention and coal overcapacity: The case of China," Energy Policy, Elsevier, vol. 101(C), pages 162-169.
    13. Tan, Ruipeng & Lin, Boqiang, 2018. "What factors lead to the decline of energy intensity in China's energy intensive industries?," Energy Economics, Elsevier, vol. 71(C), pages 213-221.
    14. Roxani Karagiannis, 2015. "A system-of-equations two-stage DEA approach for explaining capacity utilization and technical efficiency," Annals of Operations Research, Springer, vol. 227(1), pages 25-43, April.
    15. Andrews-Speed, Philip & Ma, Guo & Shao, Bingjia & Liao, Chenglin, 2005. "Economic responses to the closure of small-scale coal mines in Chongqing, China," Resources Policy, Elsevier, vol. 30(1), pages 39-54, March.
    16. Fan, Yuling & Xia, Xiaohua, 2017. "A multi-objective optimization model for energy-efficiency building envelope retrofitting plan with rooftop PV system installation and maintenance," Applied Energy, Elsevier, vol. 189(C), pages 327-335.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sun, J. & Wen, W. & Wang, M. & Zhou, P., 2022. "Optimizing the provincial target allocation scheme of renewable portfolio standards in China," Energy, Elsevier, vol. 250(C).
    2. Xu, Jiuping & Shu, Kejing & Wang, Fengjuan & Yang, Guocan, 2024. "Bi-level multi-objective distribution strategy integrating the permit trading scheme towards coal production capacity layout optimization: Case study from China," Resources Policy, Elsevier, vol. 91(C).
    3. Heinisch, Katja & Holtemöller, Oliver & Schult, Christoph, 2021. "Power generation and structural change: Quantifying economic effects of the coal phase-out in Germany," Energy Economics, Elsevier, vol. 95(C).
    4. Wang, Xiaofei & Miao, Chenglin & Wang, Chongmei & Yin, Dawei & Chen, Shaojie & Chen, Lei & Li, Ke, 2022. "Coal production capacity allocation based on efficiency perspective—taking production mines in Shandong Province as an example," Energy Policy, Elsevier, vol. 171(C).
    5. Jorrit Gosens & Alex Turnbull & Frank Jotzo, 2021. "An installation-level model of China's coal sector shows how its decarbonization and energy security plans will reduce overseas coal imports," Papers 2112.06357, arXiv.org, revised Dec 2021.
    6. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2022. "Exploring the multidimensional effects of China's coal de-capacity policy: A regression discontinuity design," Resources Policy, Elsevier, vol. 75(C).
    7. Nugent, Jeffrey B. & Lu, Jiaxuan, 2021. "China's outward foreign direct investment in the Belt and Road Initiative: What are the motives for Chinese firms to invest?," China Economic Review, Elsevier, vol. 68(C).
    8. Wu, Haitao & Wang, Bingjie & Lu, Mingyue & Irfan, Muhammad & Miao, Xin & Luo, Shiyue & Hao, Yu, 2023. "The strategy to achieve zero‑carbon in agricultural sector: Does digitalization matter under the background of COP26 targets?," Energy Economics, Elsevier, vol. 126(C).
    9. Yang, Qing & Zhang, Lei & Zou, Shaohui & Zhang, Jinsuo, 2020. "Intertemporal optimization of the coal production capacity in China in terms of uncertain demand, economy, environment, and energy security," Energy Policy, Elsevier, vol. 139(C).
    10. Liu, Dandan & Wang, Delu & Mao, Jinqi, 2023. "Study on policy synergy strategy of the central government and local governments in the process of coal de-capacity: Based on a two-stage evolutionary game method," Resources Policy, Elsevier, vol. 80(C).
    11. Xu, Jie & Lv, Tao & Hou, Xiaoran & Deng, Xu & Liu, Feng, 2021. "Provincial allocation of renewable portfolio standard in China based on efficiency and fairness principles," Renewable Energy, Elsevier, vol. 179(C), pages 1233-1245.
    12. Yihao Tian & Lijin Ding & Bin Yang & Feng Peng, 2022. "The Effects of De-Capacity Policy on Steel and Coal Firms’ Profitability: Evidence from China’s Listed Companies," Energies, MDPI, vol. 15(12), pages 1-17, June.
    13. Guo, Jinling & Gao, Junlian & Yan, Kejia & Zhang, Bo, 2023. "Unintended mitigation benefits of China's coal de-capacity policies on methane emissions," Energy Policy, Elsevier, vol. 181(C).
    14. Mo, Jianlei & Tu, Qiang & Wang, Jianing, 2023. "Carbon pricing and enterprise productivity-The role of price stabilization mechanism," Energy Economics, Elsevier, vol. 120(C).
    15. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2021. "Exploring the dilemma of overcapacity governance in China's coal industry: A tripartite evolutionary game model," Resources Policy, Elsevier, vol. 71(C).
    16. Xuguang Hao & Mei Song & Yunan Feng & Wen Zhang, 2019. "De-Capacity Policy Effect on China’s Coal Industry," Energies, MDPI, vol. 12(12), pages 1-16, June.
    17. Xue, Liming & Zhang, Wenjie & Zheng, Zhixue & Liu, Zhe & Meng, Shuo & Li, Huaqing & Du, Yulin, 2021. "Measurement and influential factors of the efficiency of coal resources of China’s provinces: Based on Bootstrap-DEA and Tobit," Energy, Elsevier, vol. 221(C).
    18. Yao, Xilong & Wang, Hualing & Shao, Shuai & Li, Xiaoyu & Guo, Zhi, 2022. "“Booster” or “obstacle”: Can coal capacity cut policies moderate the resource curse effect? Evidence from Shanxi (China)," Resources Policy, Elsevier, vol. 75(C).
    19. Jianming Xi & Hanran Wu & Bo Li & Jingyu Liu, 2020. "A Quantitative Analysis of the Optimal Energy Policy from the Perspective of China’s Supply-Side Reform," Sustainability, MDPI, vol. 12(12), pages 1-13, June.
    20. Wang, Delu & Liu, Yifei & Wang, Yadong & Shi, Xunpeng & Song, Xuefeng, 2020. "Allocation of coal de-capacity quota among provinces in China: A bi-level multi-objective combinatorial optimization approach," Energy Economics, Elsevier, vol. 87(C).
    21. Li, Zheng-Zheng & Su, Chi-Wei & Chang, Tsangyao & Lobonţ, Oana-Ramona, 2022. "Policy-driven or market-driven? Evidence from steam coal price bubbles in China," Resources Policy, Elsevier, vol. 78(C).
    22. Zhang, Weike & Meng, Jia & Tian, Xiaoli, 2020. "Does de-capacity policy enhance the total factor productivity of China's coal companies? A Regression Discontinuity design," Resources Policy, Elsevier, vol. 68(C).
    23. Zhang, Rui & Qie, Xiaotong & Hu, Yanyong & Chen, Xue, 2022. "Does de-capacity policy promote the efficient and green development of the coal industry? –Based on the evidence of China," Resources Policy, Elsevier, vol. 77(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Delu & Liu, Yifei & Wang, Yadong & Shi, Xunpeng & Song, Xuefeng, 2020. "Allocation of coal de-capacity quota among provinces in China: A bi-level multi-objective combinatorial optimization approach," Energy Economics, Elsevier, vol. 87(C).
    2. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2021. "Exploring the dilemma of overcapacity governance in China's coal industry: A tripartite evolutionary game model," Resources Policy, Elsevier, vol. 71(C).
    3. Zhang, Weike & Meng, Jia & Tian, Xiaoli, 2020. "Does de-capacity policy enhance the total factor productivity of China's coal companies? A Regression Discontinuity design," Resources Policy, Elsevier, vol. 68(C).
    4. Yu, Shiwei & Lu, Tingwei & Hu, Xing & Liu, Lancui & Wei, Yi-Ming, 2021. "Determinants of overcapacity in China’s renewable energy industry: Evidence from wind, photovoltaic, and biomass energy enterprises," Energy Economics, Elsevier, vol. 97(C).
    5. Xu, Jiuping & Shu, Kejing & Wang, Fengjuan & Yang, Guocan, 2024. "Bi-level multi-objective distribution strategy integrating the permit trading scheme towards coal production capacity layout optimization: Case study from China," Resources Policy, Elsevier, vol. 91(C).
    6. Yang, Qing & Zhang, Lei & Zou, Shaohui & Zhang, Jinsuo, 2020. "Intertemporal optimization of the coal production capacity in China in terms of uncertain demand, economy, environment, and energy security," Energy Policy, Elsevier, vol. 139(C).
    7. Wang, Di & Shen, Ye & Zhao, Yueying & He, Wei & Liu, Xue & Qian, Xiangyan & Lv, Tao, 2020. "Integrated assessment and obstacle factor diagnosis of China's scientific coal production capacity based on the PSR sustainability framework," Resources Policy, Elsevier, vol. 68(C).
    8. Yihao Tian & Lijin Ding & Bin Yang & Feng Peng, 2022. "The Effects of De-Capacity Policy on Steel and Coal Firms’ Profitability: Evidence from China’s Listed Companies," Energies, MDPI, vol. 15(12), pages 1-17, June.
    9. Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018. "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, vol. 70(C), pages 244-257.
    10. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2022. "Exploring the multidimensional effects of China's coal de-capacity policy: A regression discontinuity design," Resources Policy, Elsevier, vol. 75(C).
    11. 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.
    12. Liu, Dandan & Wang, Delu, 2022. "Evaluation of the synergy degree of industrial de-capacity policies based on text mining: A case study of China's coal industry," Resources Policy, Elsevier, vol. 76(C).
    13. Xiang, Hongjin & Kuang, Yanxiang & He, Hongbo & Yao, Shujie, 2022. "Could tariffs reduce overcapacity and environmental pollution? Evidence from China’s adjustment of tariffs on coal," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 129-144.
    14. 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).
    15. Yang, Qing & Zhang, Lei & Zhang, Jinsuo & Zou, Shaohui, 2021. "System simulation and policy optimization of China's coal production capacity deviation in terms of the economy, environment, and energy security," Resources Policy, Elsevier, vol. 74(C).
    16. Wang, Xiaolei & Deng, Renxin & Yang, Yufang, 2023. "The spatiotemporal effect of factor price distortion on capacity utilization in China’s iron and steel industry," Resources Policy, Elsevier, vol. 86(PA).
    17. Dong, Kaiqiang & Sun, Wei, 2022. "Would the market mechanism cause the formation of overcapacity?: Evidence from Chinese listed firms of manufacturing industry," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 97-113.
    18. Zhang, Rui & Qie, Xiaotong & Hu, Yanyong & Chen, Xue, 2022. "Does de-capacity policy promote the efficient and green development of the coal industry? –Based on the evidence of China," Resources Policy, Elsevier, vol. 77(C).
    19. Li Ji & Tian Zeng, 2022. "Environmental “Fee-to-Tax” and Heavy Pollution Enterprises to De-Capacity," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    20. Yao, Xilong & Wang, Hualing & Shao, Shuai & Li, Xiaoyu & Guo, Zhi, 2022. "“Booster” or “obstacle”: Can coal capacity cut policies moderate the resource curse effect? Evidence from Shanxi (China)," Resources Policy, Elsevier, vol. 75(C).

    More about this item

    Keywords

    De-capacity; Target allocation; Multi-objective nonlinear optimization; Coal industry;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • L72 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Other Nonrenewable Resources

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:78:y:2019:i:c:p:109-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.