Synergistic Development Mode of Digital Finance and Green Finance: Driving Factors and Transition Pathways

Unlike traditional research that assumes uniform development patterns or uses subjective quantile or geographic divisions, this study employs a finite mixture model to endogenously cluster different regions of China into distinct development patterns based on the similarity of their conditional distributions. Using a coupling coordination degree model to measure the synergistic development level of digital finance and green finance across 30 Chinese provinces (autonomous regions, municipalities) from 2012 to 2022, it investigates the driving factors. The results show: (1) Synergistic development between digital finance and green finance exhibits an overall upward trend with significant heterogeneity. Development patterns can be categorized as low-level, medium-level, and high-level. Economic development helps explain the formation of these growth patterns. (2) Marketization level promotes synergistic development across all patterns. However, the driving roles of traditional financial development level, data factorization level, human capital, traditional technological level, digital technological level, industrial structure, government intervention, and internet development level vary across different stages and patterns. (3) In total, 28 regions experienced pattern transitions in their synergistic development paths, which can be classified into leading, normal, and lagging development paths. The key finding of this study lies in uncovering the imbalanced development of digital finance and green finance synergy in parts of China. It provides targeted policy recommendations for synergistic development across regions and offers references for achieving high-quality economic development.