How Does the Digital Economy Affect Carbon Emissions? Evidence from Panel Smooth Transition Regression Model

Wei Jiang (), Xiaoyong Wu (), Qili Yu () and Mingming Leng ()
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Wei Jiang: Qingdao University
Xiaoyong Wu: Qingdao University
Qili Yu: Qingdao University
Mingming Leng: Lingnan University

Journal of the Knowledge Economy, 2025, vol. 16, issue 2, No 118, 9219-9245

Abstract: 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.

Keywords: Digital economy; Carbon emissions; Panel smooth transition regression model; Nonlinear effect (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-02262-8

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