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Coal lumps vs. electrons: How do Chinese bulk energy transport decisions affect the global steam coal market?

Author

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  • Paulus, Moritz
  • Trüby, Johannes

Abstract

This paper demonstrates the ways in which different Chinese bulk energy transport strategies affect the future steam coal market in China and in the rest of the world. An increase in Chinese demand for steam coal will lead to a growing need for additional domestic infrastructure as production hubs and demand centers are spatially separated, and domestic transport costs could influence the future Chinese steam coal supply mix. If domestic transport capacity is available only at elevated costs, Chinese power generators could turn to the global trade markets and further increase steam coal imports. Increased Chinese imports could then yield significant changes in steam coal market economics on a global scale. This effect is analyzed in China, where coal is mainly transported by railway, and in another setting where coal energy is transported as electricity. For this purpose, a spatial equilibrium model for the global steam coal market has been developed. One major finding is that if coal is converted into electricity early in the supply chain, worldwide marginal costs of supply are lower than if coal is transported via railway. Furthermore, China's dependence on international imports is significantly reduced in this context. Allocation of welfare changes particularly in favor of Chinese consumers while rents of international producers decrease.

Suggested Citation

  • Paulus, Moritz & Trüby, Johannes, 2011. "Coal lumps vs. electrons: How do Chinese bulk energy transport decisions affect the global steam coal market?," Energy Economics, Elsevier, vol. 33(6), pages 1127-1137.
  • Handle: RePEc:eee:eneeco:v:33:y:2011:i:6:p:1127-1137
    DOI: 10.1016/j.eneco.2011.02.006
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    References listed on IDEAS

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    Cited by:

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    2. Song, Yunting & Wang, Nuo, 2019. "Exploring temporal and spatial evolution of global coal supply-demand and flow structure," Energy, Elsevier, vol. 168(C), pages 1073-1080.
    3. Stephan Nagl, 2013. "Prices vs. Quantities: Incentives for Renewable Power Generation - Numerical Analysis for the European Power Market," EWI Working Papers 2013-4, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    4. Wang, Chengjin & Ducruet, César, 2014. "Transport corridors and regional balance in China: the case of coal trade and logistics," Journal of Transport Geography, Elsevier, vol. 40(C), pages 3-16.
    5. Wang, Wenya & Fan, L.W. & Zhou, P., 2022. "Evolution of global fossil fuel trade dependencies," Energy, Elsevier, vol. 238(PC).
    6. Haftendorn, C. & Kemfert, C. & Holz, F., 2012. "What about coal? Interactions between climate policies and the global steam coal market until 2030," Energy Policy, Elsevier, vol. 48(C), pages 274-283.
    7. Grave, Katharina & Paulus, Moritz & Lindenberger, Dietmar, 2012. "A method for estimating security of electricity supply from intermittent sources: Scenarios for Germany until 203011The paper is based on a study of the Institute of Energy Economics at the University of Cologne, funded by the German Federal Ministry," Energy Policy, Elsevier, vol. 46(C), pages 193-202.
    8. Christian Growitsch & Harald Hecking & Timo Panke, 2014. "Supply Disruptions and Regional Price Effects in a Spatial Oligopoly—An Application to the Global Gas Market," Review of International Economics, Wiley Blackwell, vol. 22(5), pages 944-975, November.
    9. Chengjin Wang & César Ducruet, 2014. "Transport corridors and regional balance in China: the case of coal trade and logistics," Post-Print halshs-01069149, HAL.
    10. Moritz Paulus, 2012. "How are investment decisions in the steam coal market affected by demand uncertainty and buyer-side market power?," EWI Working Papers 2012-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    11. Maryke C. Rademeyer, 2021. "Investigating the outcome for South African coal supply to the domestic market when faced with declining demand for exported coal," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(3), pages 441-453, October.
    12. Philipp M. Richter & Roman Mendelevitch & Frank Jotzo, 2018. "Coal taxes as supply-side climate policy: a rationale for major exporters?," Climatic Change, Springer, vol. 150(1), pages 43-56, September.
    13. Trüby, Johannes, 2013. "Strategic behaviour in international metallurgical coal markets," Energy Economics, Elsevier, vol. 36(C), pages 147-157.
    14. 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.
    15. Franziska Holz & Clemens Haftendorn & Roman Mendelevitch & Christian von Hirschhausen, 2016. "A Model of the International Steam Coal Market (COALMOD-World)," Data Documentation 85, DIW Berlin, German Institute for Economic Research.
    16. Maryke Rademeyer & Richard Minnitt & Rosemary Falcon, 2021. "Multi-product coal distribution and price discovery for the domestic market via mathematical optimisation," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(1), pages 113-126, April.
    17. Clemens Haftendorn & Franziska Holz & Claudia Kemfert & Christian von Hirschhausen, 2013. "Global steam coal markets until 2030: perspectives on production, trade and consumption under increasing carbon constraints," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 4, pages 103-122, Edward Elgar Publishing.
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    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General

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