Author(s)

FengJuan Lu, ZhengTao Chen^*

Affiliation(s)

College of Economics, Guangxi Minzu University, Nanning 530000, Guangxi, China.

Corresponding Author

ZhengTao Chen

ABSTRACT

This study investigates the impact of the digital economy on new quality productivity in China from a machine learning perspective. Employing panel data from 30 Chinese provinces spanning 2012-2021, the research utilizes various econometric and machine learning techniques, including fixed effects models, generalized method of moments, random forest, mediation analysis, and threshold regression. The findings reveal a robust positive relationship between digital economy development and new quality productivity, with green innovation playing a crucial mediating role. The random forest model uncovers a nonlinear relationship, where the marginal contribution of the digital economy to productivity exhibits an inverted U-shaped pattern. Furthermore, the threshold regression analysis highlights the moderating effect of innovation, with the productivity-enhancing impact of the digital economy amplified at higher levels of innovation. These results underscore the transformative potential of digital technologies in driving high-quality economic growth, while emphasizing the importance of fostering green innovation and an enabling innovation ecosystem. The study offers valuable insights for policymakers, advocating for a holistic, innovation-centric approach to harnessing the digital economy as a catalyst for sustainable development.

KEYWORDS

Digital economy; New quality productivity; Green innovation; Machine learning; Threshold effect

CITE THIS PAPER

FengJuan Lu, ZhengTao Chen. Harnessing the transformative potential of the digital economy for high-quality growth: evidence from China. Trends in Social Sciences and Humanities Research. 2024, 2(10): 52-62. DOI: https://doi.org/10.61784/tsshr3099.

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