Quantitative evaluation of pilot low-carbon policies based on text mining

Abstract

[Objective] This study conducted a multidimensional quantitative evaluation of pilot low-carbon policies to provide a more effective basis for the formulation and optimization of such policies, and help achieve the dual carbon goals. [Methods] Based on the policy text, text mining was used to obtain low-carbon pilot keywords, and then the PMC index model was constructed to conduct a multidimensional quantitative evaluation of 128 pilot low-carbon policies in China. [Results] The results show that: (1) The overall design of pilot low-carbon policies was good, and the average PMC index was 5.69, which belongs to the good level. The average values of the PMC index and policy response strength index showed an increasing trend from 2010 to 2018. (2) There were great differences in the design level of different pilot policies, as shown by the standard deviation of PMC index was 1.89. The proportion of non-excellent policies was as high as 57.03%, and there were some prominent problems involving lack of long-term planning, low policy level and effectiveness level, insufficient incentive guarantee, and insufficient attention to science and technology. (3) The average PMC index values of pilot low-carbon policies developed by the central government was higher than that of local policies. Most of the central policies were good, but the response intensity index values of local policies were higher than that of the central policies, and excellent policies were dominated by local policies. Both the policy quality and response intensity index of acceptable policies need to be improved. (4) The average PMC index values of the policies of important pilot cities was higher than that of the whole sample and local policies,because the participants of important pilot city policies were clearer, the policy functions were more perfect, and the incentive guarantee system was more sound. The policies of important pilot cities provide a guidance for other cities to optimize the pilot policies. [Conclusion] In the future, pilot low-carbon policies should be optimized and promoted by clarifying participants, improving policy functions and incentive guarantees, enhancing policy timeliness, and promoting the construction of low-carbon legal system.

Keywords

• |pilot low-carbon policy|text mining|pmc index model|policy assessment|policy optimization