Abstract
Green finance has become an important reform force to promote the sustainable development of China's economy. Therefore, it has a great significance for in-depth analysis of the advantages and disadvantages of regional green finance development, to further promote it by clarifying and predicting the regional differences and dynamic evolution trends. Based on this, this paper will select the relevant index from 2001 to 2020 to construct China Green Finance Core Network (CGFCN) in different years by using Space-L method at the first, then analyze its network characteristics and spatial evolution pattern in depth, and finally predict the future development trend of CGFCN by link prediction. The research results show that: firstly, the evolution of CGFCN is mainly divided into three stages: rapid development, stable development and optimal development, and the closeness of CGFCN is constantly improving. Besides, two strong relationship networks are gradually forming, that is Beijing-Tianjin region and the Yangtze River Detla region. Secondly, with the development of green finance, the community division has changed. It is mainly divided into four communities, named the Beijing-Tianjin-Hebei leading community, the eastern provincial community, the Yangtze River Delta community and the central and southern joint community. Different communities will have different integration in different periods. Thirdly, the future development direction of green finance network is mainly Beijing-Tianjin-Hebei region and Yangtze River Delta regions, and their outward radiation are mainly shown in the eastern coastal and central regions, which also have strong development potential. In this regard, it is proposed to coordinate development across provinces to speed up the "urban integration" of green finance services; Establish an efficient community development mechanism and promote the interconnection of green finance markets and infrastructure between different regions; Strengthen the resource flow among regions and coordinate the resource competition of green finance.
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Data availability
The data of this study come from the China Statistical Yearbook, Statistical Yearbook of each province, China Insurance Yearbook and National Bureau of Statistics.
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Funding
This study is supported by Guizhou Key Laboratory of Big Data Statistical Analysis (No.[2019]5103) and the Guizhou University of Finance and Economics 2021 Annual Research Grant for Current Students Project No. (2021ZXSY03).
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Data curation: Shihui Chen, Kexin Wang; Methodology: Linyu Du, Jun Fu; Resources: Wenqian Xiao; Supervision: Lina Peng; Writing-original draft: Yiming Du, Juan Liang; Writing—review & editing: Rui Ding.
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Ding, R., Du, Y., Du, L. et al. Green finance network evolution and prediction: fresh evidence from China. Environ Sci Pollut Res 30, 68241–68257 (2023). https://doi.org/10.1007/s11356-023-27183-y
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DOI: https://doi.org/10.1007/s11356-023-27183-y