Using panel data from 30 provinces in China from 2005 to 2020, this paper uses a spatial double difference model to evaluate the policy impact of the “grain-to-feed” policy on feed grain production in pilot areas and adjacent spatial areas. Research has found that the “grain-to-feed” policy has a significant impact on the feed grain production in pilot areas and can significantly increase the feed grain production in pilot areas by about 2.71 million tons. The “grain-to-feed” policy has strengthened the positive connection between pilot areas and adjacent pilot areas, increased feed grain production, and has a significant spatial spillover effect. Robustness analysis shows that whether using different methods to measure spatial adjacency or using different standards to distribute subsidies, the “grain-to-feed” policy can significantly increase feed grain production, narrow the supply and demand gap of feed grain, and ensure feed grain security. Further analysis shows that the “grain-to-feed” policy can not only ensure the security of feed grain for the current and next periods but also promote the increase in farmers’ income, which is long-term and sustainable. Compared with non-pilot areas, the “grain-to-feed” policy can mitigate the negative impact of wage–price signals on feed grain production in pilot areas. It is recommended that government departments accelerate the transformation of food security concepts, establish a “Big Food Perspective”, gradually promote the pilot of the “grain-to-feed” policy nationwide, increase the subsidy amount of the “grain-to-feed” policy, increase financial support for scientific and technological research and achievement transformation in the field of feed grain, prevent the impact of economic price signal fluctuations on feed grain production, and effectively ensure the security of feed grain in China.

The agricultural sector is the second-largest contributor to greenhouse gas emissions, and reducing agricultural carbon emissions has increasingly become a focus of international climate policy. Using panel data from 30 Chinese provinces (2011–2023), our analysis based on a two-way fixed-effects model demonstrates that the development of state-owned enterprises (SOEs) significantly reduces agricultural carbon emissions. Analysis via a chain mediating model reveals that the development of SOEs first enhances agricultural and green technological innovation, which subsequently facilitates resource conservation (reducing the use of pesticides, fertilizers, agricultural films, and agricultural diesel), ultimately leading to a reduction in agricultural carbon emissions. Heterogeneity analysis indicates that the effect of SOE development on agricultural carbon emissions reduction is more pronounced in provinces outside the Yangtze River Economic Belt and in regions with large-scale farmland operations. Threshold analysis further indicates that the effect of SOE development on reducing agricultural carbon emissions weakens when population aging exceeds a certain threshold but strengthens when the agricultural industrial structure surpasses another. Finally, analysis using a spatial Durbin model indicates that the development of SOEs significantly reduces agricultural carbon emissions in neighboring regions through spatial spillover effects. Future research should develop differentiated policies for agricultural carbon emissions based on spatial patterns, population aging, farm size, and industrial structure. It should also explore interprovincial low-carbon cooperation models involving SOEs and develop benefit-sharing mechanisms to enhance spatial spillovers.