Coupling Coordination Analysis between Total Factor Productivity and Digital Economy in China’s Agriculture

This study aims to systematically analyze the coupling and coordinated development between the digital economy (DE) and total factor productivity (TFP) in China’s agricultural sector, focusing on their impact on regional agricultural advancement. Using a comprehensive dataset from 31 Chinese provinces covering the period from 2014 to 2021, we apply the EBM model, entropy weight method, and coupling coordination degree model to assess TFP-DE interactions. To capture spatial-temporal dynamics and regional disparities, we employ kernel density estimation, Moran’s I index, the Dagum Gini coefficient, and an obstacle degree model. The findings reveal an initial phase of “multipolarization” in TFP-DE coordination, which gradually stabilizes towards preliminary coordination levels. Despite this progress, significant regional imbalances persist, particularly in central and western provinces where “low-low” clusters dominate, in contrast to the “high-high” clusters in eastern regions. While disparities in coordination have narrowed in eastern areas, they continue to widen across central and western regions. The primary obstacles have shifted from foundational infrastructure to challenges directly associated with DE and TFP. This study underscores the necessity of region-specific policies to address these disparities, particularly in underdeveloped areas, to enhance agricultural productivity through digital integration. The findings provide a strategic foundation for policymakers to foster balanced and sustainable growth, contributing to China’s broader goals for agricultural modernization.