[Impact of China's Digital Economy on the Spatial Correlation Network of Carbon Emissions from a Carbon Transfer Perspective]

The digital economy serves as the core driver for industrial structure transformation and upgrading， playing a critical leveraging role in advancing carbon emission reduction. Based on panel data from 30 Chinese provinces spanning from 2010 to 2022， this study constructs a spatial correlation network of carbon emissions and employs integrated methodologies of complex network analysis and econometric modeling to empirically examine the dynamic impact of the digital economy on this network. The results reveal three key findings： First， the spatial correlation network exhibited significant temporal volatility with macro-level spatial heterogeneity and polarization， demonstrating a pronounced core-periphery structure. Second， hierarchical and reciprocal patterns dominated the network's microstructure， indicating its preliminary developmental stage and substantial structural optimization potential. Third， the digital economy's impact on carbon emission correlations showed spatiotemporal heterogeneity： a one-unit increase in the digital economy index elevated a region's probability of becoming a sending node in the network by a factor of 8.473 while reducing its likelihood of being a receiving node to 0.338 times the original state. Nevertheless， region-specific attributes and developmental stages yielded more nuanced effects. The in-depth investigation into how the digital economy influences carbon emission networks provides actionable insights for coordinated regional climate governance.