IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v184y2024ics0301421523004536.html
   My bibliography  Save this article

Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies

Author

Listed:
  • Nie, Yan
  • Zhang, Guoxing
  • Zhong, Luhao
  • Su, Bin
  • Xi, Xi

Abstract

The gap in electricity consumption between urban and rural households under the influence of electricity price reform policies remain largely unexplored. We construct a mechanistic framework for the impact of the electricity price reform policy on the electricity consumption behaviour of urban and rural residents, and evaluates the carbon reduction effect of the policy guidance through data obtained from a large-scale household energy consumption survey from January 2020 to May 2021. The results of the study show the followings: (1) The daily electricity consumption of rural households is larger and more volatile than that of urban households. However, the growth rate of household electricity consumption of urban residents is larger than that of rural residents. (2) The electricity price reform policy mainly influences urban and rural residents' household electricity consumption behaviour by driving demand motives and comfort motives. (3) Under policy intervention, rural residents’ household energy consumption will decline at a faster rate, and urban residents' total household energy consumption will decline faster before 2025 and then remain in a stable state. To achieve the carbon peak and carbon neutrality goals of the energy system, the low-carbon energy use behaviour of residents can be guided by differentiated policies.

Suggested Citation

  • Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
  • Handle: RePEc:eee:enepol:v:184:y:2024:i:c:s0301421523004536
    DOI: 10.1016/j.enpol.2023.113868
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421523004536
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2023.113868?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. Sun, Chuanwang & Lin, Boqiang, 2013. "Reforming residential electricity tariff in China: Block tariffs pricing approach," Energy Policy, Elsevier, vol. 60(C), pages 741-752.
    2. Ming-Zhi Gao, Anton & Fan, Chien-Te & Kai, Ji-Jung & Liao, Chao-Ning, 2015. "Sustainable photovoltaic technology development: step-by-step guidance for countries facing PV proliferation turmoil under the feed-in tariff scheme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 156-163.
    3. Wang, Zhaohua & Sun, Yefei & Wang, Bo, 2020. "Policy cognition is more effective than step tariff in promoting electricity saving behaviour of residents," Energy Policy, Elsevier, vol. 139(C).
    4. Lanlan Li & Xinpei Song & Jingjing Li & Ke Li & Jianling Jiao, 2023. "The impacts of temperature on residential electricity consumption in Anhui, China: does the electricity price matter?," Climatic Change, Springer, vol. 176(3), pages 1-26, March.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Sapci, Onur & Considine, Timothy, 2014. "The link between environmental attitudes and energy consumption behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 52(C), pages 29-34.
    7. Yoo, Seung-Hoon & Lee, Joo Suk & Kwak, Seung-Jun, 2007. "Estimation of residential electricity demand function in Seoul by correction for sample selection bias," Energy Policy, Elsevier, vol. 35(11), pages 5702-5707, November.
    Full references (including those not matched with items on IDEAS)

    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, Yao & Lin, Boqiang & Li, Minyang, 2021. "Is household electricity saving a virtuous circle? A case study of the first-tier cities in China," Applied Energy, Elsevier, vol. 285(C).
    2. Jia, Jun-Jun & Guo, Jin & Wei, Chu, 2021. "Elasticities of residential electricity demand in China under increasing-block pricing constraint: New estimation using household survey data," Energy Policy, Elsevier, vol. 156(C).
    3. 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).
    4. Lin, Boqiang & Chen, Xing, 2018. "Is the implementation of the Increasing Block Electricity Prices policy really effective?--- Evidence based on the analysis of synthetic control method," Energy, Elsevier, vol. 163(C), pages 734-750.
    5. Zhu, Penghu & Lin, Boqiang, 2022. "Do the elderly consume more energy? Evidence from the retirement policy in urban China," Energy Policy, Elsevier, vol. 165(C).
    6. Lin, Boqiang & Lan, Tianxu, 2023. "Progress of increasing-block electricity pricing policy implementation in China's first-tier cities and the impact of resident policy perception," Energy Policy, Elsevier, vol. 177(C).
    7. Liu, Chang & Lin, Boqiang, 2020. "Is increasing-block electricity pricing effectively carried out in China? A case study in Shanghai and Shenzhen," Energy Policy, Elsevier, vol. 138(C).
    8. Klege, Rebecca A. & Amuakwa-Mensah, Franklin & Visser, Martine, 2022. "Tenancy and energy choices in Rwanda. A replication and extension study," World Development Perspectives, Elsevier, vol. 26(C).
    9. Federica Cucchiella & Idiano D’Adamo & Paolo Rosa, 2015. "Industrial Photovoltaic Systems: An Economic Analysis in Non-Subsidized Electricity Markets," Energies, MDPI, vol. 8(11), pages 1-16, November.
    10. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    11. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    12. Xie, Li & Kong, Chun, 2023. "The social welfare effect of electricity user connection price policy reform," Applied Energy, Elsevier, vol. 346(C).
    13. Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024. "On the (Mis)Use of Machine Learning with Panel Data," Papers 2411.09218, arXiv.org.
    14. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    15. Qi Huang & Aihua Jiang & Yu Zeng & Jianan Xu, 2022. "Community Flexible Load Dispatching Model Based on Herd Mentality," Energies, MDPI, vol. 15(13), pages 1-18, June.
    16. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    17. Arbues, Fernando & Villanu´a, Inmaculada & Barberán Ortí, Ramón, 2010. "Household size and residential water demand: an empirical approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(1), pages 1-20.
    18. Wang, Zhaohua & Sun, Yefei & Wang, Bo, 2020. "Policy cognition is more effective than step tariff in promoting electricity saving behaviour of residents," Energy Policy, Elsevier, vol. 139(C).
    19. Wang, Bo & Deng, Nana & Li, Haoxiang & Zhao, Wenhui & Liu, Jie & Wang, Zhaohua, 2021. "Effect and mechanism of monetary incentives and moral suasion on residential peak-hour electricity usage," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    20. Xiong, Yongqing & Yang, Xiaohan, 2016. "Government subsidies for the Chinese photovoltaic industry," Energy Policy, Elsevier, vol. 99(C), pages 111-119.

    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:184:y:2024:i:c:s0301421523004536. 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.