Research on GGDP evaluation system based on DPSIR and Grey prediction model

Abstract

The GGDP (Green GDP) index is revised and innovated based on the traditional GDP index. It not only inherits the advantages that the traditional GDP can measure the economic level well, but also makes up for the shortcomings that the resources and environment are not considered in the measurement process of the traditional GDP. This paper concentrates on the problem that the traditional GDP algorithm cannot provide credit for natural resources. By combining the United Nations GGDP theory, various factors such as environment, climate and GDP were considered to get the formula for calculating GGDP. Based on DPSIR model, GGDP evaluation index system is constructed from five aspects: driving force, pressure, state, influence and response. The China’s data set is selected for the specific numerical calculation of GGDP, the GGDP evaluation index system is analyzed, and a simple grey prediction is made for the future trend. This paper takes China as an example for application analysis, the evaluation indicators reflect the development level of China's GGDP consistent with the actual situation, indicating that the GGDP evaluation indicator system based on the DPSIR model is scientific and operable. The average relative error of the grey prediction model is 6.776%, which means that the DPSIR model has a good fitting effect.