This study applies Fisher’s investment framework to investigate how patient capital affects firms’ green total factor productivity (GTFP). Using panel data from Chinese listed companies over the period 2008–2023, we measure firm-level GTFP by employing a non-radial SBM directional distance function combined with the Malmquist–Luenberger productivity index. Our analysis, based on two-way fixed-effects models and instrumental variable regressions, reveals that an increase in patient capital significantly enhances firms’ green total factor productivity. Mechanism analysis indicates that this improvement arises from reduced financing costs as well as increased green R&D investment. Furthermore, the positive impact is particularly pronounced among small and medium-sized enterprises, non-state-owned firms, and pollution-intensive industries. The findings suggest that encouraging the transition from short-term speculative capital toward long-term patient capital can effectively improve firms’ environmental efficiency. Thus, policy efforts should be directed towards expanding the supply of patient capital to promote corporate sustainability and accelerate the low-carbon economic transition without compromising economic efficiency.

The deep integration of digital technologies with agricultural production is reshaping how rural land is used and offers new opportunities for narrowing the urban–rural gap in land use efficiency. Building on theoretical analysis, this study uses panel data for 700 Chinese counties from 2010 to 2024, treats the Digital Agriculture Innovation and Application Base pilot program as a quasi-natural experiment, and applies a double machine learning model to examine the effect of smart agriculture construction on the urban–rural gap in land use efficiency. The results show the following: (1) Smart agriculture construction significantly narrows the urban–rural gap in land use efficiency, with channel evidence pointing to agricultural technological progress, improved capital allocation, and agricultural industrial upgrading. (2) The policy effect is statistically significant only in formerly poverty-stricken counties, counties with higher land-transfer rates, and counties with stronger digital foundations, while Fisher permutation tests do not establish statistically significant cross-group differences. (3) Decomposition results show that the program raises rural land use efficiency and the rural marginal returns to capital and labor while leaving the corresponding urban indicators statistically unchanged, so the observed convergence is driven primarily by rural catch-up rather than urban decline. From a factor allocation perspective, this study clarifies how smart agriculture construction can rebalance urban–rural land resource use while identifying the statistical limits of the heterogeneity and channel evidence.