基于合成控制法的中国城市生活垃圾 强制分类政策效果.

Measuring and feeding back on the implementation effects of China’ s domestic waste classification policies is of great significance to the formulation and improvement of these policies. From the front-end perspective of an individual’ s knowledge, attitude, and behavior, the policy effect of the compulsory classification of domestic waste in China is intuitive, sustainable, and implementable. This research focused on the support willingness and execution willingness of urban residents to the policy of compulsory classification of domestic waste. Compiling a special emotional dictionary for the policy of compulsory classification of domestic waste and using text mining and sentiment analysis, we obtained the attitudes of Shanghai residents who were the first to implement this policy in China. Based on the synthetic control method, a number of cities that had not implemented this policy were selected as the control group for fitting, to simulate the situation in Shanghai where the policy was not implemented and to compare with the effect of the current compulsory classification policy to highlight the implementation effects of the compulsory policy. Finally, we used the data of each city to conduct a robustness test in time and region to prove the reliability of the conclusions obtained. The results of the study showed that, since the proposal for compulsory waste classification in China, although the support and execution willingness of urban residents had fluctuated, the overall trend was upward, and the execution willingness was generally lower than the support willingness. The policy of compulsory classification of domestic waste significantly increased the support and execution willingness of Shanghai residents, although its level of practice was still relatively low. The quality and size of the population played a negative role in the moderating effect of the policy effects, weakening the promotion effect of the policy on residents’ support and execution willingness. Finally, corresponding policy recommendations are put forward based on the analysis results. [ABSTRACT FROM AUTHOR]