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Has China’s coal consumption already peaked? A demand-side analysis based on hybrid prediction models


  • Wang, Ce
  • Li, Bing-Bing
  • Liang, Qiao-Mei
  • Wang, Jin-Cheng


To deal simultaneously with the environmental problems caused by the current high-intensity exploitation and extensive use of coal resources, it is necessary to perform a scientific prediction of the trend and, especially, the peak of China’s coal demand. Based on the historical data on coal consumption and four primary factors (economic growth, energy structure, investment, and industrial structure) during the period of 1981–2015, this study established a hybrid model for coal demand prediction, using particle swarm optimization and cointegration methods. According to the prediction results combined with the actual statistics, in the business-as-usual scenario, China’s coal demand had peaked in 2014, then a downward trend started with an average annual decline rate of 5.85% for 2016 to 2020. However, future coal demand will keep increasing in the pessimism scenario. And in the optimism scenario, coal demand will decline much faster than the business-as-usual scenario. Sensitive analysis on four influential factors shows that coal demand is more sensitive to changes in investment and industrial structure, and more emphasis should be put on the supply and the demand side of coal industry.

Suggested Citation

  • Wang, Ce & Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2018. "Has China’s coal consumption already peaked? A demand-side analysis based on hybrid prediction models," Energy, Elsevier, vol. 162(C), pages 272-281.
  • Handle: RePEc:eee:energy:v:162:y:2018:i:c:p:272-281
    DOI: 10.1016/

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    References listed on IDEAS

    1. Crompton, Paul & Wu, Yanrui, 2005. "Energy consumption in China: past trends and future directions," Energy Economics, Elsevier, vol. 27(1), pages 195-208, January.
    2. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    3. Naiming Xie & Alan Pearman, 2014. "Forecasting energy consumption in China following instigation of an energy-saving policy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 639-659, November.
    4. Apergis, Nicholas & Payne, James E., 2010. "The causal dynamics between coal consumption and growth: Evidence from emerging market economies," Applied Energy, Elsevier, vol. 87(6), pages 1972-1977, June.
    5. Wang, Xiaoyu & Luo, Dongkun & Zhao, Xu & Sun, Zhu, 2018. "Estimates of energy consumption in China using a self-adaptive multi-verse optimizer-based support vector machine with rolling cross-validation," Energy, Elsevier, vol. 152(C), pages 539-548.
    6. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    7. Hao, Yu & Zhang, Zong-Yong & Liao, Hua & Wei, Yi-Ming, 2015. "China’s farewell to coal: A forecast of coal consumption through 2020," Energy Policy, Elsevier, vol. 86(C), pages 444-455.
    8. Yu, Shi-wei & Zhu, Ke-jun, 2012. "A hybrid procedure for energy demand forecasting in China," Energy, Elsevier, vol. 37(1), pages 396-404.
    9. Bloch, Harry & Rafiq, Shuddhasattwa & Salim, Ruhul, 2012. "Coal consumption, CO2 emission and economic growth in China: Empirical evidence and policy responses," Energy Economics, Elsevier, vol. 34(2), pages 518-528.
    10. Li, Raymond & Leung, Guy C.K., 2012. "Coal consumption and economic growth in China," Energy Policy, Elsevier, vol. 40(C), pages 438-443.
    11. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    12. Liang, Qiao-Mei & Fan, Ying & Wei, Yi-Ming, 2007. "Multi-regional input-output model for regional energy requirements and CO2 emissions in China," Energy Policy, Elsevier, vol. 35(3), pages 1685-1700, March.
    13. Xiong, Ping-ping & Dang, Yao-guo & Yao, Tian-xiang & Wang, Zheng-xin, 2014. "Optimal modeling and forecasting of the energy consumption and production in China," Energy, Elsevier, vol. 77(C), pages 623-634.
    14. Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2015. "A comparative study on prediction methods for China's medium- and long-term coal demand," Energy, Elsevier, vol. 93(P2), pages 1671-1683.
    15. Bildirici, Melike E. & Bakirtas, Tahsin, 2014. "The relationship among oil, natural gas and coal consumption and economic growth in BRICTS (Brazil, Russian, India, China, Turkey and South Africa) countries," Energy, Elsevier, vol. 65(C), pages 134-144.
    16. Qi, Ye & Stern, Nicholas & Wu, Tong & Lu, Jiaqi & Green, Fergus, 2016. "China's post-coal growth," LSE Research Online Documents on Economics 67503, London School of Economics and Political Science, LSE Library.
    17. Pao, H.T., 2009. "Forecasting energy consumption in Taiwan using hybrid nonlinear models," Energy, Elsevier, vol. 34(10), pages 1438-1446.
    18. Wang, Qiang & Li, Rongrong, 2017. "Decline in China's coal consumption: An evidence of peak coal or a temporary blip?," Energy Policy, Elsevier, vol. 108(C), pages 696-701.
    19. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
    20. Fan, Ying & Xia, Yan, 2012. "Exploring energy consumption and demand in China," Energy, Elsevier, vol. 40(1), pages 23-30.
    21. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    22. Lin Chan, Hing & Kam Lee, Shu, 1997. "Modelling and forecasting the demand for coal in China," Energy Economics, Elsevier, vol. 19(3), pages 271-287, July.
    23. Xiao, Ling & Wang, Jianzhou & Dong, Yao & Wu, Jie, 2015. "Combined forecasting models for wind energy forecasting: A case study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 271-288.
    24. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
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    Cited by:

    1. Shuhui Yang & Xuefeng Cui, 2019. "Building Regional Sustainable Development Scenarios with the SSP Framework," Sustainability, MDPI, Open Access Journal, vol. 11(20), pages 1-13, October.
    2. Qiao, Hui & Chen, Siyu & Dong, Xiucheng & Dong, Kangyin, 2019. "Has China's coal consumption actually reached its peak? National and regional analysis considering cross-sectional dependence and heterogeneity," Energy Economics, Elsevier, vol. 84(C).

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    Coal demand; Hybrid model; Peak; Forecast; China;


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