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Study on decoupling analysis between energy consumption and economic growth in Liaoning Province

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  • Dong, Bai
  • Zhang, Ming
  • Mu, Hailin
  • Su, Xuanming

Abstract

Since 1978, Liaoning province has experienced spectacular economic growth, which has led to more energy consumption. The purpose of this paper is to explore the decoupling status between energy consumption and economic growth in Liaoning Province. Firstly, the generalized LMDI method is used to explore the driving forces governing production energy consumption in Liaoning province. Then, the combination of Tapio decoupling indicator and generalized LMDI method is utilized to study what the decoupling status occurred in Liaoning Province and why the decoupling status appeared. During the study period, only four decoupling status occurred: expansive negative decoupling, expansive coupling, weak decoupling, and strong decoupling. The energy intensity decoupling effect played a positive role in the appearance of decoupling. However, the economic structure decoupling effect and investment decoupling effect played a negative role in the appearance of decoupling. Over the study period, the energy structure decoupling effect and labour decoupling effect played a relative small role in the appearance of decoupling.

Suggested Citation

  • Dong, Bai & Zhang, Ming & Mu, Hailin & Su, Xuanming, 2016. "Study on decoupling analysis between energy consumption and economic growth in Liaoning Province," Energy Policy, Elsevier, vol. 97(C), pages 414-420.
  • Handle: RePEc:eee:enepol:v:97:y:2016:i:c:p:414-420
    DOI: 10.1016/j.enpol.2016.07.054
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    References listed on IDEAS

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    1. Climent, Francisco & Pardo, Angel, 2007. "Decoupling factors on the energy-output linkage: The Spanish case," Energy Policy, Elsevier, vol. 35(1), pages 522-528, January.
    2. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Decomposing the decoupling of CO2 emissions and economic growth in Brazil," Ecological Economics, Elsevier, vol. 70(8), pages 1459-1469, June.
    3. Tapio, Petri, 2005. "Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001," Transport Policy, Elsevier, vol. 12(2), pages 137-151, March.
    4. Diakoulaki, D. & Mandaraka, M., 2007. "Decomposition analysis for assessing the progress in decoupling industrial growth from CO2 emissions in the EU manufacturing sector," Energy Economics, Elsevier, vol. 29(4), pages 636-664, July.
    5. Zhang, Ming & Liu, Xiao & Wang, Wenwen & Zhou, Min, 2013. "Decomposition analysis of CO2 emissions from electricity generation in China," Energy Policy, Elsevier, vol. 52(C), pages 159-165.
    6. Wang, Wenwen & Liu, Xiao & Zhang, Ming & Song, Xuefeng, 2014. "Using a new generalized LMDI (logarithmic mean Divisia index) method to analyze China's energy consumption," Energy, Elsevier, vol. 67(C), pages 617-622.
    7. Zhang, Ming & Guo, Fangyan, 2013. "Analysis of rural residential commercial energy consumption in China," Energy, Elsevier, vol. 52(C), pages 222-229.
    8. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    9. Zhang, Zhongxiang, 2000. "Decoupling China's Carbon Emissions Increase from Economic Growth: An Economic Analysis and Policy Implications," World Development, Elsevier, vol. 28(4), pages 739-752, April.
    10. Ma, Chunbo & Stern, David I., 2008. "China's changing energy intensity trend: A decomposition analysis," Energy Economics, Elsevier, vol. 30(3), pages 1037-1053, May.
    11. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    12. Ren, Shenggang & Hu, Zhen, 2012. "Effects of decoupling of carbon dioxide emission by Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 43(C), pages 407-414.
    13. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    14. Ang, B.W. & Liu, Na, 2007. "Handling zero values in the logarithmic mean Divisia index decomposition approach," Energy Policy, Elsevier, vol. 35(1), pages 238-246, January.
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