Technology-driven carbon reduction: Analyzing the impact of digital technology on China's carbon emission and its mechanism

Yajun Liu, Xiuwu Zhang and Yang Shen

Technological Forecasting and Social Change, 2024, vol. 200, issue C

Abstract: The dissemination of information, knowledge spillover, intelligent monitoring, and advanced productivity provided by digital technology (DT) play an essential role in combating climate change. Whether the business model changes and economic development facilitated by digital technologies will enable China to achieve its goal of a low-carbon transition remains to be seen. Based on 269 cities in China from 2006 to 2021, the study used two-way fixed effects and instrumental variables to analyze the role of DT in carbon reduction and its indirect mechanisms. The results indicate that the wide application and deep integration of DT in the physical industry will reduce carbon emissions (CE). The mechanism analysis reveals that DT, with its efficient, integrated, and green characteristics, will help improve energy efficiency and promote green technology innovation, thereby reducing CE. Most importantly, this study innovatively reveals the role of virtual agglomeration in carbon reduction. It uses data factors with production characteristics to shift the supply and demand parties and related enterprises from physical space to cyberspace agglomeration, which plays a significant positive role in the process of reducing CE. DT has a heterogeneous effect on reducing CE, especially in the sample of urban agglomeration and resource-based cities, which is more intense. The central government's policies on digital infrastructure and CE regulation influence the role of digital technologies in reducing CE. The conclusions of this study have implications for relevant market entities and the government to fully utilise DT to accelerate the realisation of green production and cope with climate change.

Keywords: Digital economy; Digital technology; Virtual agglomeration; Carbon neutral; Industrial robot; Heteroskedasticity-based identification (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523008090

DOI: 10.1016/j.techfore.2023.123124

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