The Impact of Green Technological Innovation on Regional Carbon Emissions —— With New-Quality Productivity as the Core Driving Force

Authors

  • Yongyi Guo * School of Statistics and Data Science, Guangdong University of Finance and Economics, Guangzhou 510320, China. https://orcid.org/0000-0002-6651-1714
  • Wei Guo School of Statistics and Data Science, Guangdong University of Finance and Economics, Guangzhou 510320, China. https://orcid.org/0000-0002-1471-9804
  • Ruyi Chen School of Statistics and Data Science, Guangdong University of Finance and Economics, Guangzhou 510320, China. https://orcid.org/0009-0004-3990-8558
  • Zhe Fang School of Statistics and Data Science, Guangdong University of Finance and Economics, Guangzhou 510320, China.
  • Jinkun Huo School of Statistics and Data Science, Guangdong University of Finance and Economics, Guangzhou 510320, China.
  • Zhuo Tang School of Statistics and Data Science, Guangdong University of Finance and Economics, Guangzhou 510320, China.

https://doi.org/10.22105/masi.v3i1.86

Abstract

Against the backdrop of increasing global climate governance pressure and the accelerated advancement of China's "dual-carbon" goals, exploring the synergistic emission reduction path of green technological innovation and productivity transformation is of critical importance. This paper, centered on the theoretical core of new quality productivity, establishes a systematic analytical framework of "green technological innovation→production efficiency improvement →regional low-carbon development" to uncover the impact mechanism, spatial characteristics,and regional heterogeneity of green technological innovation on regional carbon emissions. This study utilizes panel data from 30 provinces in China from 2017 to 2021, employing a combination of mediation effect models and spatial econometric models for empirical analysis.The results indicate the following: First, green technological innovation has a significant direct inhibitory effect on regional carbon emissions by reducing carbon intensity through pathways such as fossil fuel substitution, energy structure optimization,and strengthening end-of-pipe industrial treatment. Second, new quality productivity, as measured by Total Factor Productivity (TFP), plays a partial mediating role in this relationship. Green technological innovation enhances TFP, which in turn indirectly reduces carbon emissions through improved factor utilization and industrial upgrading, thus verifying the "technological innovation→productivity improvement→carbon emission reduction" transmission mechanism. Third, the emission reduction effect exhibits significant regional heterogeneity. The inhibitory effect of green technological innovation is more pronounced in the eastern regions and areas with higher per capita GDP, whereas the western region's reduction is primarily driven by improvements in TFP. Fourth, spatial econometric analysis confirms the presence of spatial spillovers; carbon emission intensity showed significant spatial agglomeration from 2017 to 2019, and inter-regional technological collaboration and policy coordination can enhance overall reduction effects. This research reveals the intrinsic relationship between green technological innovation, new quality productivity, and carbon emissions, providing theoretical support and empirical evidence for formulating differentiated regional low-carbon policies and promoting the synergy between technological innovation and productivity transformation under the "dual-carbon" objectives.  

Keywords:

Green technological innovation, New-quality productivity, Carbon emissions, Total factor productivity, Spatial effect, Mediation effect

References

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Published

2026-03-04

Issue

Vol. 3 No. 1 (2026): Management Analytics and Social Insights (MASI)

Section

Articles

How to Cite

Guo, Y., Guo, W., Chen, R., Fang, Z., Huo, J., & Tang, Z. (2026). The Impact of Green Technological Innovation on Regional Carbon Emissions —— With New-Quality Productivity as the Core Driving Force. Management Analytics and Social Insights, 3(1), 1-16. https://doi.org/10.22105/masi.v3i1.86