The spatio-temporal evolution and dynamic progress of the coupling coordination between the digital economy and agricultural green development in China

Agricultural digitalization and green development are important for high-quality agricultural development and for achieving the dual-carbon goals of China. Using panel data from 30 provinces in China for 2013–2022, this study examines the spatio-temporal evolution, regional disparities, and dynamic transitions of the coupling coordination degree (CCD) between the digital economy (DE) and agricultural green development (AGD). The analysis combines a CCD model with Dagum Gini decomposition, kernel density estimation, and spatial Markov chain analysis. The results show several clear patterns. The national CCD increased from 0.360 to 0.553, indicating a shift from disorder to basic coordination, while the faster growth of DE than AGD points to a persistent developmental mismatch. CCD also shows clear spatial heterogeneity across the eight economic zones, and regional inequality follows a U-shaped trajectory rather than a sustained convergence path. Markov chain analysis indicates strong path dependence and low-level lock-in. Spatial Markov chain analysis further shows that neighborhood conditions significantly affect transition probabilities; high-level neighboring regions facilitate upgrading but do not guarantee sustained leapfrogging. Overall, DE–AGD coordination is a differentiated evolutionary process shaped by regional endowments, spatial spillovers, and path dependence. These results provide evidence for region-specific policies that connect agricultural digitalization with green agricultural development.