Improving agricultural green total factor productivity is important for achieving high-quality economic development and the SDGs. Digital inclusive finance, which combines the advantages of digital technology and inclusive finance, represents a new scheme that can ease credit constraints and information ambiguity in agricultural production. First, this study focused on agro-ecological functions; we incorporated total agricultural carbon sequestration and emissions extraction into the evaluation system and used the mixed-direction-distance function to calculate agricultural green total factor productivity. Then, based on panel data from 31 provinces in China collected from 2011 to 2021, we used the two-way fixed effect model, the interactive fixed effect, and the plausibly exogenous variable method to test the impact of digital financial inclusion on agricultural green total factor productivity, and its mechanism of action. The panel-corrected standard error and fixed effect Driscoll–Kraay methods were used to account for the unobserved heterogeneity and cross-section dependence in the panel data. The results showed that digital financial inclusion can significantly improve agricultural green total factor productivity. This conclusion remained valid following robustness tests using the spatial econometric model and the method of changing explanatory variables. Digital financial inclusion can improve agricultural green total factor productivity by facilitating the transfer of agricultural land. Sound digital infrastructure and strict green credit policies enhance the role of digital inclusive finance in promoting the green development of agriculture. These conclusions could help the financial sector to formulate flexible, accurate, reasonable, and appropriate financial policies and products that would support agriculture, and enhance the role of digital inclusive finance in promoting sustainable agricultural development.

Green development is the only way to realize harmonious coexistence between people and nature, so it is of great significance to create a benchmark for high-quality development. Based on the panel data of 30 provinces (except Tibet, Hong Kong, Macao, and Taiwan) in China from 2009 to 2020, the super-efficiency slacks-based measure model was used to calculate the green economic efficiency of various regions in China, and a related statistical model was used to verify the influence of different types of environmental regulation policies on green economic efficiency and the intermediary effect of innovation factor agglomeration. The results show that: (1) during the inspection period, the influence of public-participation environmental regulation on the efficiency of the green economy presents an “inverted U” trend, while command-control and market-incentive environmental regulation policies inhibit the improvement of green economic efficiency; (2) the agglomeration of innovative elements plays a significant intermediary role in the transmission path of environmental regulation affecting green economic efficiency, but the intermediary effects of different types of environmental regulation are slightly different. Finally, we discuss environmental regulation and innovative elements, and some corresponding suggestions are put forward.