Hui Guo, Xinyi Wang, He Xia, Wenjie Jiang
Enhancing agricultural green total factor productivity (AGTFP) is essential for advancing high-quality agricultural development. This study employs a super-efficiency SBM-DDF-GML model to calculate AGTFP using county-level panel data from China (2014-2023). Leveraging national digital village pilot (NDVP) programs as a quasi-natural experiment, it further applies a Difference-in-Differences (DID) approach to evaluate the impact, underlying mechanisms, and spatial spillover effects of digital village development on AGTFP. Results indicate that digital village initiatives significantly boost AGTFP. The results remain robust across multiple robustness checks and endogeneity tests, with effects primarily driven by green technological progress rather than green technological efficiency improvements. Mechanism analysis indicates that digital village development enhances AGTFP by promoting optimal labor allocation, stimulating agribusiness entrepreneurship, and expanding consumption. Heterogeneity analysis reveals that the policy effect is more pronounced in areas near provincial capitals, with high terrain undulation, and low road network density. The spatial effect during the sample period is dominated by siphoning, with only green technological progress exhibiting signs of spillover over time. This study provides new empirical evidence on how digital village development drives agricultural green transformation and offers policy implications for optimizing policy design and promoting coordinated regional development.