Effects of China's carbon generalized system of preferences on low-carbon action: A synthetic control analysis based on text mining

Abstract

Measuring the effects of China's Carbon Generalized System of Preferences (CGSP) on low-carbon action from front-end perspectives, such as residents' willingness, is intuitive and implementable. This study used text mining and sentiment analysis to obtain residents' willingness to support and implement low-carbon living in the sample cities, and constructed a counterfactual comparison unit to assess whether the implementation of CGSP enhances residents' willingness based on the synthetic control method. The results showed that the CGSP has a long-term effect on increasing residents' willingness to implement low-carbon living, but has a limited effect on increasing residents' willingness to support. Additionally, the degree of air pollution has a positive moderating effect on the implementation of CGSP, and there is a substitution effect between technological innovation capacity and policy implementation. This study provides insights for policymakers on the variations in residents' willingness to low-carbon living under the influence of CGSP, which is crucial for achieving policy optimization and building a low-carbon chain in society.