Optimizing sustainable high-quality economic development through Green Finance with robust spatial estimation

Abstract

Green finance (GF) holds significant potential in fostering high-quality economic development (HED), enhancing societal affluence consistency, and alleviating poverty by promoting sustainable development, innovation, and resilience. This study addresses environmental challenges and the promotion of sustainable economic growth through the pivotal tools of GF. We employ spatial spillover, quantile regression, and regional-wise models to derive four key findings. Firstly, baseline regression analysis reveals a noteworthy positive association between GF and HED, indicating that the adoption and utilization of green financial mechanisms significantly advance economic development while maintaining ecological sustainability. Secondly, using a spatial econometric model, this study identifies the presence of a spillover effect, showing that the positive impact of GF on HED extends beyond individual provinces and contributes to overall economic development on a broader geographical scale. Thirdly, the analysis of regional heterogeneity demonstrates that the correlation between GF and HED varies across different regions of China. Notably, a significant association between GF and HED is observed in the western region, highlighting the importance of considering regional disparities in the implementation and effectiveness of green financial policies. Lastly, through quantile regression analysis, this study uncovers non-linear relationships between GF and HED, emphasizing that the impact of green financial strategies on economic development varies across different quantiles of the economic development distribution. This study provides several practical policy implications for financial institutions and policymakers.

Keywords

• Green finance
• sustainable economic development
• regional heterogeneity
• spatial effect
• non-linear relationship
• China