Continued investment in finance and innovation is beneficial to economic development, and the joining of green system can accelerate the process of economic recovery from environmental distress. To better enhance the relationship of green finance and green innovation, it is vital to demonstrate the synergy between the two thoroughly. Thirty provinces in China are selected to examine the coupling coordination relationship between the two, specifically testing the spatial aggregation and evolutionary differences in the coupling coordination by adopting the coupling coordination degree (CCD) model, spatial autocorrelation, and kernel density estimation. Conclusions of the paper show that green finance is calculated by the EW-TOPSIS method, and the overall score of provinces is low. Using super-SBM model to evaluate green innovation, the uneven distribution of efficiency is obvious, although it is gradually increasing. The CCD in most provinces is in low-level or basic coordination, with significant regional heterogeneity. The global Moran's index becomes gradually evident with time. The local Moran scatter diagram presents a downward trend from east to west, but with more L-L aggregation provinces emerging in 2020. The center of the national kernel density curve gradually shifts to the right, indicating that the national overall synergy level is improving. Deepening the understanding of the empirical results facilitates the formulation of reasonable policies that fit the four major regions.
Keywords: Green finance; Green innovation efficiency; Kernel density estimation; Moran’s I; Super-SBM.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.