Climate volatility and market uncertainty pose significant challenges to agricultural stability. We assess whether and how agricultural industrial agglomeration shapes China’s agricultural economic resilience using province-level panel data for 2003–2023 and a transparent, entropy-weighted index spanning resistance, recovery, and adaptability. Four results stand out. First, in a two-way fixed-effects model, agglomeration is associated with higher resilience on average, and this finding remains robust across multiple robustness tests and after addressing endogeneity concerns. Second, regional subgroup analyses reveal pronounced heterogeneity, providing evidence for geographically targeted policy design. Third, mechanism analysis reveals that the agricultural research intensity serves as a partial mediator between agglomeration and resilience. Fourth, the agglomeration-resilience relationship is nonlinear—N-shaped in the aggregate, while panel quantile regressions reveal an inverted-U among low-resilience provinces and an N-shaped pattern at the median and upper end of the distribution. In an extension, global Moran’s I statistics for three alternative resilience indices reveal significant positive spatial autocorrelation, indicating that agricultural economic resilience tends to cluster geographically and that spatial spillovers are likely to be present. In conclusion, agglomeration is a net enhancer of agricultural economic resilience, but its payoffs are agglomeration- and distribution-dependent: gains taper or reverse around the mid-range for low-resilience provinces, while the median and upper segments benefit again as specialization deepens, in a setting where resilience itself is spatially clustered. Reinforcing the research channel and tailoring actions to local resilience levels are therefore pivotal.

Green finance is increasingly expected to support decarbonization while enhancing productivity, yet evidence on whether green credit bonds raise green total factor productivity (GTFP) remains limited. Using panel data for 29 provincial-level regions in China from 2016 to 2023, we compute GTFP using a slacks-based measure Malmquist–Luenberger (SBM–ML) index and estimate two-way fixed-effects models. To address endogeneity, we employ a Bartik shift–share instrumental-variable strategy. We found that green credit bonds significantly increase GTFP, with gains driven mainly by technological change (TC) rather than efficiency change (EC). The effect is stronger in eastern and western regions, in provinces that are not low-carbon pilot areas, and in regions with stronger low-carbon governance orientation. Public environmental attention directly improves GTFP but dampens the marginal effect of green credit bonds. Mechanism analyses further indicate that the low-carbon transition of the energy mix (LCEM) is an important transmission channel. Overall, these findings suggest that scaling up and better targeting green credit bonds, alongside complementary governance and public scrutiny, can accelerate China’s transition toward higher green productivity. This provides sustainability-relevant evidence that market-based green finance can support decarbonization while sustaining productivity growth, contributing to long-term sustainable development.