Adaptation and Feasibility Study of Green GDP Accounting System in China
Keywords:
SEEA-CF, Random Forest Regression Model, Gray Prediction Model, GGDP, CRITIC Weighting MethodAbstract
In recent years, with the increasing risk of global climate change, the worldwide discussion on green economy has been further intensified. In this paper, based on the central framework of SEEA, we analyze the impact of the environment on the economy from multiple perspectives and establish a green GDP accounting model. In addition, a new method combining random forest regression as well as CRITIC weighting method is used to select reasonable indicators. The accounting formula derived from this new method is used to calculate the green GDP in 2000, 2005, 2010, 2015, and 2020, and to compare the differential contribution of GGDP and GDP of the selected countries to measure the efforts made by each country for environmental protection, and the results show that it is worthwhile to adopt GGDP. This paper focuses on China as the main target for the case study and finds the strongest link between GGDP and clean energy among the indicators. The impact generated by GGDP is also discussed using the gray prediction method. Finally, a statistical approach is used to visualize the growth rate of the aging population, and it is found that the implementation of GGDP is beneficial to the environment, the economy, and the lives of citizens.
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