As countries accelerate rural digitalization, China’s agricultural sector is undergoing a critical transition toward smarter and lower-carbon development. Yet, whether digital rural development (DRD) is systematically aligned with agricultural decarbonization remains to be empirically clarified. Using provincial panel data for 30 Chinese provinces from 2001 to 2024, this study examines the relationship between DRD and agricultural carbon emission intensity (ACEI) and investigates potential mechanisms and spatial spillovers. We employ two-way fixed-effect models, mechanism tests using one-period-lagged mediators, and a spatial Durbin model (SDM) under alternative spatial weight matrices to assess robustness and spatial dependence. The results indicate that: (1) DRD is statistically significantly and negatively associated with ACEI, and this relationship remains robust across alternative specifications, subsamples, and sensitivity checks, including re-estimation excluding border regions such as Xinjiang and Xizang; (2) mechanism evidence is consistent with three observable channels—supporting agricultural R (3) ACEI exhibits pronounced spatial dependence, and DRD is associated not only with lower local ACEI but also potentially with cross-regional spillovers, although spillover inference is contingent on the specification of the spatial weight matrix; and (4) K-means clustering based on DRD and ACEI identifies four regional types (high digitization–high emissions, high digitization–low emissions, low digitization–high emissions, and low digitization–low emissions), highlighting heterogeneous constraints and differentiated policy priorities.
Liu et al. (Tue,) studied this question.