IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i7p3193-d1627664.html
   My bibliography  Save this article

The Impact of Electricity Grid Development on Economic Growth and Energy Consumption in Anhui Province: A Seemingly Unrelated Regression-Based Analysis

Author

Listed:
  • Xiaomin Shi

    (Economic Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China)

  • Xiang Gao

    (Economic Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China)

  • Rong Li

    (Economic Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China)

  • Ke Hou

    (School of Economics, Hefei University of Technology, Hefei 230601, China)

  • Yang Song

    (School of Economics, Hefei University of Technology, Hefei 230601, China)

  • Zhongjiang Lu

    (School of Economics, Hefei University of Technology, Hefei 230601, China)

Abstract

Endogeneity is an important issue that needs to be addressed in research. By integrating infrastructure into the input–output system based on a profit function framework, this paper investigates the impact of electricity infrastructure on economic development and energy consumption. Using city-level data from Anhui Province spanning 2012 to 2022 and applying seemingly unrelated regression techniques for parameter estimation, this study finds that an increase in grid density leads to a reduction in energy consumption. While the short-term effect of increased grid density may cause a decline in output, a positive long-term effect on output is observed. This study concludes that the advantages of robust power infrastructure in lowering energy intensity manifest only over an extended time horizon. Based on our findings, we provide relevant recommendations that can be applied to other regions as well.

Suggested Citation

  • Xiaomin Shi & Xiang Gao & Rong Li & Ke Hou & Yang Song & Zhongjiang Lu, 2025. "The Impact of Electricity Grid Development on Economic Growth and Energy Consumption in Anhui Province: A Seemingly Unrelated Regression-Based Analysis," Sustainability, MDPI, vol. 17(7), pages 1-20, April.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3193-:d:1627664
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/7/3193/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/7/3193/
    Download Restriction: no
    ---><---

    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:17:y:2025:i:7:p:3193-:d:1627664. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.