Abstract
This essay uses the panel smooth transition regression (PSTR) model to study how China’s digital economy affects carbon emissions, selects data from 30 provinces in China during 2011–2021, and constructs a digital economy evaluation index system for empirical analysis. As a nonlinear model, the PSTR model can more accurately reveal the linkage between the digital economy and carbon emissions. Compared with other nonlinear models, this model can obtain the conversion rate of different influence intensities in the digital economy. According to findings, digital economic growth has a significant curbing influence on carbon emissions. But as it advances to a certain point, this inhibiting impact weakens. Furthermore, the digital economy’s expansion could boost technological advancement, foreign direct investment, urbanization, and industrial structure optimization to curb carbon emissions in the early stage. Similarly, with the development of the digital economy to a certain extent, this inhibitory effect will weaken or increase. With China promoting a low-carbon economy against the backdrop of the contemporary internet age, it is essential to comprehend the effects of the digital economy on carbon emissions.
Original language | English |
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Journal | Journal of the Knowledge Economy |
Early online date | 15 Aug 2024 |
DOIs | |
Publication status | E-pub ahead of print - 15 Aug 2024 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Keywords
- Carbon emissions
- Digital economy
- Nonlinear effect
- Panel smooth transition regression model