IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-246-0_79.html

Empirical Research on the Digital Economy and Farmers’ Income in the Yellow River Basin

In: Proceedings of the 3rd International Conference on Economic Development and Business Culture (ICEDBC 2023)

Author

Listed:
  • Xinying Liu

    (Shandong University of Finance and Economic, Faculty of International Economics and Trade)

  • Mingyu Xu

    (Shandong University of Finance and Economic, Faculty of International Economics and Trade)

  • Jinran Wang

    (Shandong University of Finance and Economic, Faculty of International Economics and Trade)

Abstract

Based on the data of 96 cities circled in the Yellow River Basin from 2011 to 2019, the authors have measured the comprehensive indicators of urban digital economy in the Yellow River Basin in this paper. By applying fixed effect models, moderating effect models to evaluate the operating mechanism of digital economy on rural residents’ income in the Yellow River Basin the authors have figured out that the development of digital economy in the Yellow River Basin has significantly increased the income of the rural residents. Furthermore the adjustment effect shows that the increase of the output value of the Primary sector of the economy together with the increase of the urban-rural income gap will reduce the impact of the digital economy on the increase of rural residents’ income. Relying on these research results the authors propose that it is critical for the cities in the Yellow River Basin to improve digital infrastructure, to rearrange industrial structure, and to narrow down the urban-rural income gap.

Suggested Citation

  • Xinying Liu & Mingyu Xu & Jinran Wang, 2024. "Empirical Research on the Digital Economy and Farmers’ Income in the Yellow River Basin," Advances in Economics, Business and Management Research, in: Shehnaz Tehseen & Mohd Naseem Niaz Ahmad & Rafia Afroz (ed.), Proceedings of the 3rd International Conference on Economic Development and Business Culture (ICEDBC 2023), pages 656-661, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-246-0_79
    DOI: 10.2991/978-94-6463-246-0_79
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:advbcp:978-94-6463-246-0_79. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.