Effect of information-embedded policy tools on farmers’ low-carbon production behavior: Analysis based on a randomized controlled trial with Chinese medicinal herb growers in Qinling-Daba Mountain area - LI Huanli, XUE Caixia, LI Fuduo, JIANG Xuan (Ziyuan Kexue)
[Objective] Low-carbon production represents a key approach for the agricultural sector to facilitate the achievement of the “ dual carbon” goals, and policy interventions significantly influence farmers’low-carbon production behavior. An in-depth investigation into the effect of policy tools on farmers’ low-carbon production behavior can not only evaluate the effectiveness of existing policies but also provide data support for future policy adjustments. [Methods] Using randomized controlled trial (RCT) data collected from 793 Chinese medicinal herb growers in the Qinling-Daba Mountain area in 2022, this study explored the effect of information-embedded policy tools on farmers’ low-carbon production behavior using the binary Logit model, causal mediation analysis, and propensity score matching (PSM) method. [Results] (1) In terms of intervention effect, information-embedded policy tools generally outperformed standalone information-based or structural policy tools in promoting farmers’ low-carbon production behavior. Specifically, command-and-control tools embedded with environmental benefit information and economic incentive tools embedded with self-benefit information demonstrated the optimal intervention effects. (2) Environment-benefit information-embedded policy tools and self-benefit information-embedded policy tools influenced farmers’ low-carbon production behavior through ecological value identification and self-interest value perception, respectively. (3) Under the intervention of environment-benefit information-embedded tools, individuals’ low-carbon information processing pathways follows the central path. However, among self-benefit information-embedded tools, only the economic incentive types follows the central path, while command-and-control tools embedded with self-benefit information for individuals resulted in a dual-path mode of “peripheral path + central path”. [Conclusion] Information-embedded policy tools significantly promote farmers’ low-carbon production behavior. Therefore, when guiding farmers to develop low-carbon agriculture, the government should not only adopt both information-based and structural tools to enhance policy synergy, but also contextualize interventions by making them specific, scenario-based, and life-relevant. Furthermore, an enabling environment must be created to facilitate the value realization of farmers’ low-carbon behavior.