Agricultural subsidies and farmers' low-carbon transition in China: a stratified PSM analysis based on provincial and non-provincial low-carbon pilot areas

Introduction Against the backdrop of the full advancement of the “dual carbon” goals, food security and low-carbon production transition have become pivotal to promoting the sustainable development of agriculture. Exploring how agricultural subsidies influence farmers' low-carbon production transition holds important practical significance. Methods Based on the 2022 China Family Panel Studies (CFPS) farm household data, this paper stratifies samples by whether they are located in provincial-level low-carbon pilot areas and constructs a stratified Propensity Score Matching (PSM) model to eliminate self-selection bias. It verifies the transmission paths of cost constraint mitigation and low-carbon cognition improvement through a mediating effect model, and addresses endogeneity using the instrumental variable method to ensure the reliability of research conclusions. Results ① Agricultural subsidies significantly and positively drive farmers‘ low-carbon production transition; ② There is a synergistic effect between provincial-level pilot policies and agricultural subsidies, with the policy intensity in pilot areas being approximately 1.65 times that in non-pilot areas; ③ Subsidies exert their effects by alleviating cost constraints and raising farmers' low-carbon cognition; ④ The driving effect of agricultural subsidies is more pronounced for farmers with high human capital and those in eastern China. Discussion This paper confirms the synergistic effect between subsidies and pilot policies, providing a direction for policy optimization. The government needs to strengthen the binding of the low-carbon orientation of subsidies with food security goals, expand the scope of pilot areas, optimize supporting policies, and implement differentiated subsidies. However, due to the use of cross-sectional data, this paper fails to fully cover the dynamic changes of various low-carbon scenarios. Future research can conduct dynamic analysis and cross-regional international comparative studies using panel data.