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Determination of driving forces for China's energy consumption and regional disparities using a hybrid structural decomposition analysis

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  • Meng, Guanfei
  • Liu, Hongxun
  • Li, Jianglong
  • Sun, Chuanwang

Abstract

China receives great global attention for its energy consumption. To implement effective and fair policies to save energy, it is critical to understand what drives China's energy consumption and regional disparities. Most of previous studies failed to include indirect factors embodied in the inter-sectoral and regional input-output flows. Therefore, a hybrid structural decomposition analysis is conducted to explore drivers of energy consumption and regional disparities. The results present: (1) energy, directly or indirectly, is flowing from coastal regions to Northwest, Southwest and Central China. (2) The growth of residents' income to contribution of energy consumption is by 106.7% and 169.8% during 2002–2007 and 2007–2012, respectively. Meanwhile, the positive impact of income on energy consumption is larger in urban than rural areas, and the structure effect has a significantly negative impact on energy consumption in Northwest and Southwest regions. (3) By factors, the substitution effect non-energy to energy inputs in industry sector might bring more energy consumption. By sectors, the technological advancement of the non-industry sectors decreases energy consumption by 31.7% and 174.6% during 2002–2007 and 2007–2012, respectively. Technological advancement of industry sectors plays the most important role in increasing energy consumption across China.

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  • Meng, Guanfei & Liu, Hongxun & Li, Jianglong & Sun, Chuanwang, 2022. "Determination of driving forces for China's energy consumption and regional disparities using a hybrid structural decomposition analysis," Energy, Elsevier, vol. 239(PC).
  • Handle: RePEc:eee:energy:v:239:y:2022:i:pc:s0360544221024397
    DOI: 10.1016/j.energy.2021.122191
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    as
    1. Su, Bin & Huang, H.C. & Ang, B.W. & Zhou, P., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of sector aggregation," Energy Economics, Elsevier, vol. 32(1), pages 166-175, January.
    2. Erik Dietzenbacher & Jesper Stage, 2006. "Mixing oil and water? Using hybrid input-output tables in a Structural decomposition analysis," Economic Systems Research, Taylor & Francis Journals, vol. 18(1), pages 85-95.
    3. Lin, Gang & Jiang, Dong & Fu, Jingying & Wang, Di & Li, Xiang, 2019. "A spatial shift-share decomposition of energy consumption changes in China," Energy Policy, Elsevier, vol. 135(C).
    4. Lin, Boqiang & Kuang, Yunming, 2020. "Household heterogeneity impact of removing energy subsidies in China: Direct and indirect effect," Energy Policy, Elsevier, vol. 147(C).
    5. Wyatt, Peter, 2013. "A dwelling-level investigation into the physical and socio-economic drivers of domestic energy consumption in England," Energy Policy, Elsevier, vol. 60(C), pages 540-549.
    6. Lin, Boqiang & Xie, Chunping, 2014. "Energy substitution effect on transport industry of China-based on trans-log production function," Energy, Elsevier, vol. 67(C), pages 213-222.
    7. Si, Shuyang & Lyu, Mingjie & Lin Lawell, C.-Y. Cynthia & Chen, Song, 2018. "The effects of energy-related policies on energy consumption in China," Energy Economics, Elsevier, vol. 76(C), pages 202-227.
    8. Wang, Zhikun & Crawley, Jenny & Li, Francis G.N. & Lowe, Robert, 2020. "Sizing of district heating systems based on smart meter data: Quantifying the aggregated domestic energy demand and demand diversity in the UK," Energy, Elsevier, vol. 193(C).
    9. Yang, Yingchun & Liu, Jianghua & Lin, Yingying & Li, Qiongyuan, 2019. "The impact of urbanization on China’s residential energy consumption," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 170-182.
    10. Li, Jianglong & Lin, Boqiang, 2016. "Inter-factor/inter-fuel substitution, carbon intensity, and energy-related CO2 reduction: Empirical evidence from China," Energy Economics, Elsevier, vol. 56(C), pages 483-494.
    11. Chen, B. & Li, J.S. & Zhou, S.L. & Yang, Q. & Chen, G.Q., 2018. "GHG emissions embodied in Macao's internal energy consumption and external trade: Driving forces via decomposition analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4100-4106.
    12. Li, Zheng & Pan, Lingying & Fu, Feng & Liu, Pei & Ma, Linwei & Amorelli, Angelo, 2014. "China's regional disparities in energy consumption: An input–output analysis," Energy, Elsevier, vol. 78(C), pages 426-438.
    13. Yuehui Xia & Ting Zhang & Miaomiao Yu & Lingying Pan, 2020. "Regional Disparities and Transformation of Energy Consumption in China Based on a Hybrid Input-Output Analysis," Energies, MDPI, vol. 13(20), pages 1-27, October.
    14. Román-Collado, Rocío & Colinet, Maria José, 2018. "Is energy efficiency a driver or an inhibitor of energy consumption changes in Spain? Two decomposition approaches," Energy Policy, Elsevier, vol. 115(C), pages 409-417.
    15. Kuishuang Feng & Steven J. Davis & Laixiang Sun & Klaus Hubacek, 2015. "Drivers of the US CO2 emissions 1997–2013," Nature Communications, Nature, vol. 6(1), pages 1-8, November.
    16. Zhang, Haiyan & Lahr, Michael L., 2014. "China's energy consumption change from 1987 to 2007: A multi-regional structural decomposition analysis," Energy Policy, Elsevier, vol. 67(C), pages 682-693.
    17. Su, Bin & Ang, B.W., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of spatial aggregation," Ecological Economics, Elsevier, vol. 70(1), pages 10-18, November.
    18. 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.
    19. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    20. 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.
    21. 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.
    22. Lin, Boqiang & Kuang, Yunming, 2020. "Natural gas subsidies in the industrial sector in China: National and regional perspectives," Applied Energy, Elsevier, vol. 260(C).
    23. 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.
    24. Liu, Hongxun & Du, Kerui & Li, Jianglong, 2019. "An improved approach to estimate direct rebound effect by incorporating energy efficiency: A revisit of China's industrial energy demand," Energy Economics, Elsevier, vol. 80(C), pages 720-730.
    25. Hashemizadeh, Ali & Bui, Quocviet & Kongbuamai, Nattapan, 2021. "Unpacking the role of public debt in renewable energy consumption: New insights from the emerging countries," Energy, Elsevier, vol. 224(C).
    26. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
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    Cited by:

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    3. Zheng, Jiali & Feng, Gengzhong & Ren, Zhuanzhuan & Qi, Nengxi & Coffman, D'Maris & Zhou, Yunlai & Wang, Shouyang, 2022. "China's energy consumption and economic activity at the regional level," Energy, Elsevier, vol. 259(C).
    4. Yanli Ji & Jie Xue & Zitian Fu, 2022. "Sustainable Development of Economic Growth, Energy-Intensive Industries and Energy Consumption: Empirical Evidence from China’s Provinces," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    5. Xia, Quanzhi & Han, Mengyao & Guan, Shihui & Wu, Xiaofang & Zhang, Bo, 2022. "Tracking embodied energy flows of China's megacities via multi-scale supply chains," Energy, Elsevier, vol. 260(C).

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