IDEAS home Printed from https://ideas.repec.org/p/biw/wpaper/40.html
   My bibliography  Save this paper

Structural decomposition analysis on energy intensity changes at regional level

Author

Listed:
  • Hua Liao
  • Ce Wang
  • Zhi-Shuang Zhu
  • Xiao-Wei Ma

Abstract

As China's energy intensity fluctuated in recent years, it is necessary to examine whether this fluctuations happened at a regional level. This paper conducts a decomposition model by using the structural decomposition analysis (SDA) method at a regional level. Then this model is employed to empirically analyze the changes of Beijing's energy intensity. The conclusions are as follows: during 2002-2010, except petroleum, the energy intensity decreased and the changes were mostly attributed to the technology changes, while the final use variation actually increased the energy intensity; comparing different periods of 2002-2010, the decline rates of energy intensity for coal and hydropower were decreasing, resulting from the production technology being more energy-intensive than before; The energy intensity changes of petroleum firstly increased substantially then decreased moderately.

Suggested Citation

  • Hua Liao & Ce Wang & Zhi-Shuang Zhu & Xiao-Wei Ma, 2012. "Structural decomposition analysis on energy intensity changes at regional level," CEEP-BIT Working Papers 40, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    • Handle: RePEc:biw:wpaper:40
    as

    Download full text from publisher

    File URL: http://ceep.bit.edu.cn/docs/2018-10/20181011135744921669.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    2. Hua Liao, 2012. "China Country Report," Chapters, in: Shigeru Kimura (ed.), Analysis on Energy Saving Potential in East Asia, chapter 5, pages 115-130, Economic Research Institute for ASEAN and East Asia (ERIA).
    3. Cao, Shuyan & Xie, Gaodi & Zhen, Lin, 2010. "Total embodied energy requirements and its decomposition in China's agricultural sector," Ecological Economics, Elsevier, vol. 69(7), pages 1396-1404, May.
    4. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    5. Yu, Huayi, 2012. "The influential factors of China's regional energy intensity and its spatial linkages: 1988–2007," Energy Policy, Elsevier, vol. 45(C), pages 583-593.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hua Liao & Zhao-Yi & Ce Wang, 2013. "Divisia decomposition method and its application to changes of net oil import intensity," CEEP-BIT Working Papers 55, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    2. Ming Zhang & Yan Song & Lixia Yao, 2015. "Exploring commercial sector building energy consumption in China," 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. 75(3), pages 2673-2682, February.
    3. Ling Yang & Michael L. Lahr, 2019. "The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    4. Wang, Ce & Liao, Hua & Pan, Su-Yan & Zhao, Lu-Tao & Wei, Yi-Ming, 2014. "The fluctuations of China’s energy intensity: Biased technical change," Applied Energy, Elsevier, vol. 135(C), pages 407-414.
    5. Yan, Junna & Su, Bin, 2020. "What drive the changes in China's energy consumption and intensity during 12th Five-Year Plan period?," Energy Policy, Elsevier, vol. 140(C).
    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. Hongyun Han & Shu Wu, 2018. "Structural Change and Its Impact on the Energy Intensity of Agricultural Sector in China," Sustainability, MDPI, vol. 10(12), pages 1-23, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hongyun Han & Shu Wu, 2018. "Structural Change and Its Impact on the Energy Intensity of Agricultural Sector in China," Sustainability, MDPI, vol. 10(12), pages 1-23, December.
    2. Wu, Jianxin & Wu, Yanrui & Se Cheong, Tsun & Yu, Yanni, 2018. "Distribution dynamics of energy intensity in Chinese cities," Applied Energy, Elsevier, vol. 211(C), pages 875-889.
    3. Jiang, Lei & Folmer, Henk & Ji, Minhe, 2014. "The drivers of energy intensity in China: A spatial panel data approach," China Economic Review, Elsevier, vol. 31(C), pages 351-360.
    4. Zhang, Dayong & Cao, Hong & Wei, Yi-Ming, 2016. "Identifying the determinants of energy intensity in China: A Bayesian averaging approach," Applied Energy, Elsevier, vol. 168(C), pages 672-682.
    5. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    6. Huang, Junbing & Hao, Yu & Lei, Hongyan, 2018. "Indigenous versus foreign innovation and energy intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1721-1729.
    7. Huang, Junbing & Du, Dan & Tao, Qizhi, 2017. "An analysis of technological factors and energy intensity in China," Energy Policy, Elsevier, vol. 109(C), pages 1-9.
    8. Fang, Zheng & Chen, Yang, 2017. "Human capital and energy in economic growth – Evidence from Chinese provincial data," Energy Economics, Elsevier, vol. 68(C), pages 340-358.
    9. Wu, Shu & Ding, Song, 2021. "Efficiency improvement, structural change, and energy intensity reduction: Evidence from Chinese agricultural sector," Energy Economics, Elsevier, vol. 99(C).
    10. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    11. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.
    12. Dayong Zhang and David C. Broadstock, 2016. "Club Convergence in the Energy Intensity of China," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    13. Lei Jiang & Minhe Ji, 2016. "China’s Energy Intensity, Determinants and Spatial Effects," Sustainability, MDPI, vol. 8(6), pages 1-15, June.
    14. Yan, Huijie, 2015. "Provincial energy intensity in China: The role of urbanization," Energy Policy, Elsevier, vol. 86(C), pages 635-650.
    15. Jiang, Xuemei & Duan, Yuwan & Green, Christopher, 2017. "Regional disparity in energy intensity of China and the role of industrial and export structure," Resources, Conservation & Recycling, Elsevier, vol. 120(C), pages 209-218.
    16. Adom, Philip Kofi, 2015. "Business cycle and economic-wide energy intensity: The implications for energy conservation policy in Algeria," Energy, Elsevier, vol. 88(C), pages 334-350.
    17. Ma, Chunbo, 2014. "A multi-fuel, multi-sector and multi-region approach to index decomposition: An application to China's energy consumption 1995–2010," Energy Economics, Elsevier, vol. 42(C), pages 9-16.
    18. Jin, Taeyoung, 2022. "Impact of heat and electricity consumption on energy intensity: A panel data analysis," Energy, Elsevier, vol. 239(PA).
    19. Jin Zhang and David C. Broadstock, 2016. "The Causality between Energy Consumption and Economic Growth for China in a Time-varying Framework," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    20. Zhang, Dayong & Li, Jun & Ji, Qiang, 2020. "Does better access to credit help reduce energy intensity in China? Evidence from manufacturing firms," Energy Policy, Elsevier, vol. 145(C).

    More about this item

    Keywords

    Structural decomposition analysis; input-output analysis; energy intensity;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:biw:wpaper:40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Zhi-Fu Mi (email available below). General contact details of provider: https://edirc.repec.org/data/cebitcn.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.