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Will the Steam Coal Price Rebound under the New Economy Normalcy in China?


  • Xiaopeng Guo

    (School of Economics and Management, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)

  • Yanan Wei

    (School of Economics and Management, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China
    Yunnan Electric Power Science Research Institute, No. 105, Yunda Western Road, Kunming 650217, China)

  • Jiahai Yuan

    (School of Economics and Management, North China Electric Power University, No. 2 Beinong Road, Changping District, Beijing 102206, China)


The steam coal price in China has been continuously decreasing since the second half of 2012. Constant low price of coal will accelerate the development of thermal power, cause more serious air pollution problems, and bring adverse influence to China’s energy reformation in the future. Therefore, analyzing the factors underlying the phenomenon of the decreasing steam coal price is significant. In this study, we first qualitatively analyze five main factors, namely, economy, supply, demand, substitutes, and port stocks. On the basis of the relationships among these five factors, we obtain the causality diagram and the system flow diagram of coal price for further quantitative research. Then, we conduct an empirical analysis using the system dynamics (SD) method and determine the simulated price from 2012 to 2017. Finally, we discuss the running results and come to the conclusion that the steam coal price will continue to decrease under the combined actions of the five main factors and it will not rebound in the near future.

Suggested Citation

  • Xiaopeng Guo & Yanan Wei & Jiahai Yuan, 2016. "Will the Steam Coal Price Rebound under the New Economy Normalcy in China?," Energies, MDPI, vol. 9(9), pages 1-13, September.
  • Handle: RePEc:gam:jeners:v:9:y:2016:i:9:p:751-:d:78221

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    References listed on IDEAS

    1. Joëts, Marc & Mignon, Valérie, 2012. "On the link between forward energy prices: A nonlinear panel cointegration approach," Energy Economics, Elsevier, vol. 34(4), pages 1170-1175.
    2. Yuan, Chaoqing & Liu, Sifeng & Wu, Junlong, 2010. "The relationship among energy prices and energy consumption in China," Energy Policy, Elsevier, vol. 38(1), pages 197-207, January.
    3. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    4. Chi, K.C. & Reiner, D.M. & Nuttall, W.J., 2009. "Dynamics of the UK Natural Gas Industry: System Dynamics Modelling and Long-Term Energy Policy Analysis," Cambridge Working Papers in Economics 0922, Faculty of Economics, University of Cambridge.
    5. van Goor, Harm & Scholtens, Bert, 2014. "Modeling natural gas price volatility: The case of the UK gas market," Energy, Elsevier, vol. 72(C), pages 126-134.
    6. Yu, Shiwei & Wei, Yi-ming, 2012. "Prediction of China's coal production-environmental pollution based on a hybrid genetic algorithm-system dynamics model," Energy Policy, Elsevier, vol. 42(C), pages 521-529.
    7. Zaklan, Aleksandar & Cullmann, Astrid & Neumann, Anne & von Hirschhausen, Christian, 2012. "The globalization of steam coal markets and the role of logistics: An empirical analysis," Energy Economics, Elsevier, vol. 34(1), pages 105-116.
    8. Kanamura, Takashi, 2009. "A supply and demand based volatility model for energy prices," Energy Economics, Elsevier, vol. 31(5), pages 736-747, September.
    9. Ansari, Nastaran & Seifi, Abbas, 2012. "A system dynamics analysis of energy consumption and corrective policies in Iranian iron and steel industry," Energy, Elsevier, vol. 43(1), pages 334-343.
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