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Coal production forecast and low carbon policies in China

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  • Wang, Jianzhou
  • Dong, Yao
  • Wu, Jie
  • Mu, Ren
  • Jiang, He
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    Abstract

    With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0301421511005143
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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 39 (2011)
    Issue (Month): 10 (October)
    Pages: 5970-5979

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    Handle: RePEc:eee:enepol:v:39:y:2011:i:10:p:5970-5979

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    Web page: http://www.elsevier.com/locate/enpol

    Related research

    Keywords: Grey theory Coal production Carbon emissions reductions;

    References

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    1. Lin, Bo-qiang & Liu, Jiang-hua, 2010. "Estimating coal production peak and trends of coal imports in China," Energy Policy, Elsevier, vol. 38(1), pages 512-519, January.
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    Cited by:
    1. Wang, Jianliang & Feng, Lianyong & Tverberg, Gail E., 2013. "An analysis of China's coal supply and its impact on China's future economic growth," Energy Policy, Elsevier, vol. 57(C), pages 542-551.

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