IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i17p4648-d261152.html
   My bibliography  Save this article

What is Currently Driving the Growth of China’s Household Electricity Consumption? A Clustering and Decomposition Analysis

Author

Listed:
  • Ming Meng

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Shucheng Wu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Jin Zhou

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Xinfang Wang

    (School of Chemical Engineering, University of Birmingham, Edgbaston, B15 2TT Birmingham, UK)

Abstract

The rapid growth of household electricity consumption is threatening the sustainable development of China’s economy and environment because of its impacts on the operation efficiency of the electric power system. To recognize the driving factors of the consumption growth and offer policy implications, based on the consumption-related data of 2015 and 2016, this research used the rank sum ratio (RSR) method to divide China’s 30 provinces into 5 groups and a logarithmic mean Divisia index (LMDI) algorithm to decompose the composition growth of each group into the quantitative contribution of each driving factor. The following conclusions were drawn from the empirical analysis. (1) The Yangtze basin is the most vigorous region of consumption growth and should be principally monitored. (2) Climate conditions have a remarkable impact on consumption growth and should be a key consideration when making differentiated household electricity policies. (3) The rebound effect has already appeared in a few of the most developed regions. Electricity price is an effective measure in dealing with this effect. (4) The improvement of the income level is the most important driving factor for consumption growth. (5) For provinces with high growth vitality, the change in the burden level of electricity expenditure prompts consumption growth. However, for provinces with low growth vitality, the situations are opposite. (6) The impacts of electricity price and population on consumption growth are negligible.

Suggested Citation

  • Ming Meng & Shucheng Wu & Jin Zhou & Xinfang Wang, 2019. "What is Currently Driving the Growth of China’s Household Electricity Consumption? A Clustering and Decomposition Analysis," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4648-:d:261152
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/17/4648/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/17/4648/
    Download Restriction: no
    ---><---

    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. Fu, Xin & Zeng, Xiao-Jun & Feng, Pengpeng & Cai, Xiuwen, 2018. "Clustering-based short-term load forecasting for residential electricity under the increasing-block pricing tariffs in China," Energy, Elsevier, vol. 165(PB), pages 76-89.
    3. He, Xiaoping & Reiner, David, 2016. "Electricity demand and basic needs: Empirical evidence from China's households," Energy Policy, Elsevier, vol. 90(C), pages 212-221.
    4. Wang, Zhaohua & Lu, Milin & Wang, Jian-Cai, 2014. "Direct rebound effect on urban residential electricity use: An empirical study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 124-132.
    5. 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.
    6. Dongxiao Niu & Si Li & Shuyu Dai, 2018. "Comprehensive Evaluation for Operating Efficiency of Electricity Retail Companies Based on the Improved TOPSIS Method and LSSVM Optimized by Modified Ant Colony Algorithm from the View of Sustainable ," Sustainability, MDPI, vol. 10(3), pages 1-26, March.
    7. Xu, X.Y. & Ang, B.W., 2014. "Analysing residential energy consumption using index decomposition analysis," Applied Energy, Elsevier, vol. 113(C), pages 342-351.
    8. Cheng, Shulei & Wu, Yinyin & Chen, Hua & Chen, Jiandong & Song, Malin & Hou, Wenxuan, 2019. "Determinants of changes in electricity generation intensity among different power sectors," Energy Policy, Elsevier, vol. 130(C), pages 389-408.
    9. Meng, Ming & Wang, Lixue & Shang, Wei, 2018. "Decomposition and forecasting analysis of China's household electricity consumption using three-dimensional decomposition and hybrid trend extrapolation models," Energy, Elsevier, vol. 165(PA), pages 143-152.
    10. Hualong Yang & Xuefei Ma, 2019. "Uncovering CO 2 Emissions Patterns from China-Oriented International Maritime Transport: Decomposition and Decoupling Analysis," Sustainability, MDPI, vol. 11(10), pages 1-19, May.
    11. Lu Jiang & Xingpeng Chen & Bing Xue, 2019. "Features, Driving Forces and Transition of the Household Energy Consumption in China: A Review," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    12. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Multilevel LMDI decomposition of changes in aggregate energy consumption. A cross country analysis in the EU-27," Energy Policy, Elsevier, vol. 68(C), pages 576-584.
    13. Khanna, Nina Zheng & Guo, Jin & Zheng, Xinye, 2016. "Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey," Energy Policy, Elsevier, vol. 95(C), pages 113-125.
    14. Zhang, Ming & Song, Yan & Li, Peng & Li, Huanan, 2016. "Study on affecting factors of residential energy consumption in urban and rural Jiangsu," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 330-337.
    15. Liu, Dan, 2017. "Evaluating the multi-period efficiency of East Asia airport companies," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 71-82.
    16. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    17. Cheng Li & Xiaojing Zhang, 2017. "Renminbi Internationalization in the New Normal: Progress, Determinants and Policy Discussions," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 25(2), pages 22-44, March.
    18. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
    19. Berkhout, Peter H. G. & Muskens, Jos C. & W. Velthuijsen, Jan, 2000. "Defining the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 425-432, June.
    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. Meiki Permana & Eny Rochaida & Muhammad Saleh Mire & Rahcmad Budi Suharto, 2021. "Measurement of Sustainable Development with Electrification of Households in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 87-99.

    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. Fan, Jing-Li & Zhang, Yue-Jun & Wang, Bing, 2017. "The impact of urbanization on residential energy consumption in China: An aggregated and disaggregated analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 220-233.
    2. Meng, Ming & Wang, Lixue & Shang, Wei, 2018. "Decomposition and forecasting analysis of China's household electricity consumption using three-dimensional decomposition and hybrid trend extrapolation models," Energy, Elsevier, vol. 165(PA), pages 143-152.
    3. Trotta, Gianluca, 2020. "Assessing energy efficiency improvements and related energy security and climate benefits in Finland: An ex post multi-sectoral decomposition analysis," Energy Economics, Elsevier, vol. 86(C).
    4. Román-Collado, Rocío & Colinet, María José, 2018. "Are labour productivity and residential living standards drivers of the energy consumption changes?," Energy Economics, Elsevier, vol. 74(C), pages 746-756.
    5. 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.
    6. Lin, Boqiang & Wang, Yao, 2020. "Analyzing the elasticity and subsidy to reform the residential electricity tariffs in China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 189-206.
    7. Jincai Zhao & Qianqian Liu, 2021. "Examining the Driving Factors of Urban Residential Carbon Intensity Using the LMDI Method: Evidence from China’s County-Level Cities," IJERPH, MDPI, vol. 18(8), pages 1-18, April.
    8. Yong Yang & Junsong Jia & Chundi Chen, 2020. "Residential Energy-Related CO 2 Emissions in China’s Less Developed Regions: A Case Study of Jiangxi," Sustainability, MDPI, vol. 12(5), pages 1-28, March.
    9. Vélez-Henao, Johan-Andrés & García-Mazo, Claudia-Maria & Freire-González, Jaume & Vivanco, David Font, 2020. "Environmental rebound effect of energy efficiency improvements in Colombian households," Energy Policy, Elsevier, vol. 145(C).
    10. Lei Liu & Ke Wang & Shanshan Wang & Ruiqin Zhang & Xiaoyan Tang, 2019. "Exploring the Driving Forces and Reduction Potential of Industrial Energy-Related CO 2 Emissions during 2001–2030: A Case Study for Henan Province, China," Sustainability, MDPI, vol. 11(4), pages 1-25, February.
    11. Zha, Donglan & Chen, Qian & Wang, Lijun, 2022. "Exploring carbon rebound effects in Chinese households’ consumption: A simulation analysis based on a multi-regional input–output framework," Applied Energy, Elsevier, vol. 313(C).
    12. Jain, Princy & Goswami, Binoy, 2021. "Energy efficiency in South Asia: Trends and determinants," Energy, Elsevier, vol. 221(C).
    13. Hongguang Nie & René Kemp & Véronique Vasseur, 2020. "Exploring the Changing Gap of Residential Energy Consumption per Capita in China and the Netherlands: A Comparative Analysis of Driving Forces," Sustainability, MDPI, vol. 12(11), pages 1-17, June.
    14. 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.
    15. 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).
    16. Shao, Shuai & Yang, Lili & Gan, Chunhui & Cao, Jianhua & Geng, Yong & Guan, Dabo, 2016. "Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 516-536.
    17. 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.
    18. Wang, Xiaolei & Wei, Chunxin & Wang, Yanhua, 2022. "Does the current tiered electricity pricing structure still restrain electricity consumption in China's residential sector?," Energy Policy, Elsevier, vol. 165(C).
    19. Sofia Tsemekidi Tzeiranaki & Paolo Bertoldi & Francesca Diluiso & Luca Castellazzi & Marina Economidou & Nicola Labanca & Tiago Ribeiro Serrenho & Paolo Zangheri, 2019. "Analysis of the EU Residential Energy Consumption: Trends and Determinants," Energies, MDPI, vol. 12(6), pages 1-27, March.
    20. Yong Yang & Junsong Jia & Adam T. Devlin & Yangming Zhou & Dongming Xie & Min Ju, 2020. "Decoupling and Decomposition Analysis of Residential Energy Consumption from Economic Growth during 2000–2017: A Comparative Study of Urban and Rural Guangdong, China," Energies, MDPI, vol. 13(17), pages 1-21, August.

    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:gam:jsusta:v:11:y:2019:i:17:p:4648-:d:261152. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.