IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v135y2019ics0301421519306214.html
   My bibliography  Save this article

A spatial shift-share decomposition of energy consumption changes in China

Author

Listed:
  • Lin, Gang
  • Jiang, Dong
  • Fu, Jingying
  • Wang, Di
  • Li, Xiang

Abstract

The objective of this paper is to investigate the changes in the regional energy consumption at the provincial level in China from 2007 to 2016 by introducing a spatial shift-share decomposition approach to measure the neighborhood effect on the regional energy efficiency change through the establishment of a spatial weight matrix considering the geographical and economic proximity. Using this decomposition method, the regional advantage (or disadvantage) in energy efficiency can be revealed, excluding the influence of neighborhood performance in terms of energy efficiency. The results indicate that a shift from energy intensive industrial productions toward the less energy intensive service sector occurs in almost all provinces of China over the period observed; there is significant spatial differentiation on the spatial decomposition of the efficiency change component across provinces, and the changes in energy efficiency in provinces of Jing-Jin-Ji, Yangtze River Delta, Chengdu-Chongqing, Guanzhong Plain, Pan-Pearl River Delta city agglomeration and the three provinces in Northeast China are mainly affected by the neighborhood effect. Our empirical findings suggest that energy policy making should be more concerned about the spatial correlation and coupling effects of energy consumption, especially in the national urban agglomeration of China.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:enepol:v:135:y:2019:i:c:s0301421519306214
    DOI: 10.1016/j.enpol.2019.111034
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421519306214
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2019.111034?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Giuseppe Espa & Danila Filipponi & Diego Giuliani & Davide Piacentino, 2014. "Decomposing regional business change at plant level in Italy: A novel spatial shift-share approach," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 113-135, November.
    3. Xu, X.Y. & Ang, B.W., 2014. "Analysing residential energy consumption using index decomposition analysis," Applied Energy, Elsevier, vol. 113(C), pages 342-351.
    4. Grossi, Luigi & Mussini, Mauro, 2018. "A spatial shift-share decomposition of electricity consumption changes across Italian regions," Energy Policy, Elsevier, vol. 113(C), pages 278-293.
    5. 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.
    6. Polenske, Karen R. & Lin, Xiannuan, 1993. "Conserving energy to reduce carbon dioxide emissions in China," Structural Change and Economic Dynamics, Elsevier, vol. 4(2), pages 249-265, December.
    7. Rutger Hoekstra & Bernhard Michel & Sangwon Suh, 2016. "The emission cost of international sourcing: using structural decomposition analysis to calculate the contribution of international sourcing to CO 2 -emission growth," Economic Systems Research, Taylor & Francis Journals, vol. 28(2), pages 151-167, June.
    8. Roberto Ezcurra & Pedro Pascual & Manuel Rapún, 2007. "Spatial Inequality in Productivity in the European Union: Sectoral and Regional Factors," International Regional Science Review, , vol. 30(4), pages 384-407, October.
    9. Edgar S. Dunn, 1960. "A Statistical And Analytical Technique For Regional Analysis," Papers in Regional Science, Wiley Blackwell, vol. 6(1), pages 97-112, January.
    10. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    11. Nie, Hongguang & Kemp, René, 2014. "Index decomposition analysis of residential energy consumption in China: 2002–2010," Applied Energy, Elsevier, vol. 121(C), pages 10-19.
    12. Wang, Chao & Zhang, Xinyi & Vilela, André L.M. & Liu, Chao & Stanley, H. Eugene, 2019. "Industrial structure upgrading and the impact of the capital market from 1998 to 2015: A spatial econometric analysis in Chinese regions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 189-201.
    13. Esteban, J., 2000. "Regional convergence in Europe and the industry mix: a shift-share analysis," Regional Science and Urban Economics, Elsevier, vol. 30(3), pages 353-364, May.
    14. 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.
    15. 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.
    16. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    17. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    18. Ang, B.W. & Huang, H.C. & Mu, A.R., 2009. "Properties and linkages of some index decomposition analysis methods," Energy Policy, Elsevier, vol. 37(11), pages 4624-4632, November.
    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. Miguel Blanco & Marcos Ferasso & Lydia Bares, 2021. "Evaluation of the Effects on Regional Production and Employment in Spain of the Renewable Energy Plan 2011–2020," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    2. Xue, Liming & Li, Huaqing & Shen, Wenlong & Zhao, Xiangyi & Liu, Zhe & Zheng, Zhixue & Hu, Jie & Meng, Shuo, 2023. "Applying GeoDetector to disentangle the contributions of the 4-As evaluation indicators to the spatial differentiation of coal resource security," Energy Policy, Elsevier, vol. 173(C).
    3. Yan, Junna & Su, Bin, 2020. "Spatial differences in energy performance among four municipalities of China: From both the aggregate and final demand perspectives," Energy, Elsevier, vol. 204(C).
    4. Bangjun, Wang & Linyu, Cui & Feng, Ji & Yue, Wang, 2023. "Research on club convergence effect and its influencing factors of per capita energy consumption: Evidence from the data of 243 prefecture-level cities in China," Energy, Elsevier, vol. 263(PB).
    5. You Zheng & Jianzhong Xiao & Jinhua Cheng, 2020. "Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security," IJERPH, MDPI, vol. 17(19), pages 1-18, September.
    6. Ruxu Sheng & Juntian Du & Songqi Liu & Changan Wang & Zidi Wang & Xiaoqian Liu, 2021. "Solar Photovoltaic Investment Changes across China Regions Using a Spatial Shift-Share Analysis," Energies, MDPI, vol. 14(19), pages 1-14, October.
    7. 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).
    8. Ruxu Sheng & Rong Zhou & Ying Zhang & Zidi Wang, 2021. "Green Investment Changes in China: A Shift-Share Analysis," IJERPH, MDPI, vol. 18(12), pages 1-15, June.

    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. 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.
    2. Xuankai Deng & Yanhua Yu & Yanfang Liu, 2015. "Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011," Energies, MDPI, vol. 8(6), pages 1-22, June.
    3. Li, Jin & Hu, Shanying, 2017. "History and future of the coal and coal chemical industry in China," Resources, Conservation & Recycling, Elsevier, vol. 124(C), pages 13-24.
    4. Duran, Elisa & Aravena, Claudia & Aguilar, Renato, 2015. "Analysis and decomposition of energy consumption in the Chilean industry," Energy Policy, Elsevier, vol. 86(C), pages 552-561.
    5. Chao Bao & Ruowen Liu, 2019. "Electricity Consumption Changes across China’s Provinces Using A Spatial Shift-Share Decomposition Model," Sustainability, MDPI, vol. 11(9), pages 1-15, April.
    6. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    7. Wang, Qunwei & Hang, Ye & Su, Bin & Zhou, Peng, 2018. "Contributions to sector-level carbon intensity change: An integrated decomposition analysis," Energy Economics, Elsevier, vol. 70(C), pages 12-25.
    8. Li, Tianxiang & Baležentis, Tomas & Makutėnienė, Daiva & Streimikiene, Dalia & Kriščiukaitienė, Irena, 2016. "Energy-related CO2 emission in European Union agriculture: Driving forces and possibilities for reduction," Applied Energy, Elsevier, vol. 180(C), pages 682-694.
    9. Jialing Zou & Weidong Liu & Zhipeng Tang, 2017. "Analysis of Factors Contributing to Changes in Energy Consumption in Tangshan City between 2007 and 2012," Sustainability, MDPI, vol. 9(3), pages 1-14, March.
    10. Yun-Hsun Huang & Jung-Hua Wu & Hao-Syuan Huang, 2021. "Analyzing the Driving Forces behind CO 2 Emissions in Energy-Resource-Poor and Fossil-Fuel-Centered Economies: Case Studies from Taiwan, Japan, and South Korea," Energies, MDPI, vol. 14(17), pages 1-14, August.
    11. Banie Naser Outchiri, 2020. "Contributing to better energy and environmental analyses: how accurate are decomposition analysis results?," Cahiers de recherche 20-11, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    12. Huang, Yun-Hsun, 2020. "Examining impact factors of residential electricity consumption in Taiwan using index decomposition analysis based on end-use level data," Energy, Elsevier, vol. 213(C).
    13. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    14. Edyta Sidorczuk-Pietraszko, 2020. "Spatial Differences in Carbon Intensity in Polish Households," Energies, MDPI, vol. 13(12), pages 1-21, June.
    15. Hardt, Lukas & Owen, Anne & Brockway, Paul & Heun, Matthew K. & Barrett, John & Taylor, Peter G. & Foxon, Timothy J., 2018. "Untangling the drivers of energy reduction in the UK productive sectors: Efficiency or offshoring?," Applied Energy, Elsevier, vol. 223(C), pages 124-133.
    16. Zhong, Sheng, 2018. "Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD," Energy Policy, Elsevier, vol. 122(C), pages 655-667.
    17. Grossi, Luigi & Mussini, Mauro, 2018. "A spatial shift-share decomposition of electricity consumption changes across Italian regions," Energy Policy, Elsevier, vol. 113(C), pages 278-293.
    18. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Multiplicative structural decomposition analysis of energy and emission intensities: Some methodological issues," Energy, Elsevier, vol. 123(C), pages 47-63.
    19. Fei Wang & Changjian Wang & Yongxian Su & Lixia Jin & Yang Wang & Xinlin Zhang, 2017. "Decomposition Analysis of Carbon Emission Factors from Energy Consumption in Guangdong Province from 1990 to 2014," Sustainability, MDPI, vol. 9(2), pages 1-15, February.
    20. Wang, Qunwei & Hang, Ye & Zhou, P. & Wang, Yizhong, 2016. "Decoupling and attribution analysis of industrial carbon emissions in Taiwan," Energy, Elsevier, vol. 113(C), pages 728-738.

    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:eee:enepol:v:135:y:2019:i:c:s0301421519306214. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    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.