Author
Listed:
- Jinjiang Chen
(School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China)
- Changqing Guo
(School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China)
- Xueyu Bai
(School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China)
- Ruizhen Liu
(School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China)
Abstract
Faced with increasingly severe resource shortages and environmental pressures, exploring the impact of the digital economy on green and low-carbon development and its potential mechanisms is of great significance. Drawing on a comprehensive panel dataset spanning the decade from 2014 to 2023, this study examines 11 provincial administrative regions situated within the Yangtze River Economic Belt in China, systematically examining the effects and underlying pathways of the digital economy on green and low-carbon development. We construct an evaluation index system for the digital economy and green and low-carbon development, and use a two-way fixed effects model, a moderating effect model, and a threshold regression model for empirical analysis. Empirical results show that the digital economy significantly promotes green and low-carbon development, and this conclusion remains robust after a series of robustness tests. Mechanism analysis indicates that green technology innovation plays a significant moderating role, amplifying the environmental benefits of the digital economy; industrial structure upgrading exhibits a double threshold effect, with the promoting effect of the digital economy on green and low-carbon development increasing as the threshold is exceeded. Heterogeneity analysis shows that the ecological effects of the digital economy are significant in the midstream and southwest cluster and in areas with high factor allocation efficiency. We conclude that optimizing the environment for digital economic development, emphasizing innovation in digital green technologies, and implementing differentiated regional and structural policies can achieve a coordinated advancement of digital transformation and green and low-carbon development, providing valuable empirical evidence and policy implications for regional sustainable development.
Suggested Citation
Jinjiang Chen & Changqing Guo & Xueyu Bai & Ruizhen Liu, 2026.
"How the Digital Economy Shapes Green and Low-Carbon Development in the Yangtze River Economic Belt,"
Sustainability, MDPI, vol. 18(8), pages 1-22, April.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:8:p:3659-:d:1915761
Download full text from publisher
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:18:y:2026:i:8:p:3659-:d:1915761. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address
(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.