Using panel data from 26 cities in the Yangtze River Delta from 2014 to 2024, a comprehensive Financial Risk Index integrating banking, debt, housing, and capital-market indicators is constructed and analyzed through a coupled S Study on Spatiotemporal Evolution and Regional Control of Financial Risks in the Yangtze River Delta Based on SDM-GWRpatial Durbin Model (SDM) and Geographically Weighted Regression (GWR) framework. The results reveal significant positive spatial correlation of financial risk, with “high–high” clusters centered on Shanghai, Nanjing, and Hangzhou and “low–low” clusters concentrated in parts of Anhui and Zhejiang. SDM effect decomposition identifies housing-price growth and leverage ratio as primary cross-regional spillover channels whose impacts attenuate with distance from the core. GWR further demonstrates spatial non-stationarity: industrial upgrading and fiscal self-sufficiency exert stronger stabilizing effects in core cities, whereas debt risk dominates peripheral areas. The combined SDM–GWR model achieves superior explanatory power and predictive accuracy (R² = 0.81) compared with conventional approaches. These findings provide empirical evidence for dynamic, region-specific financial-risk governance in the context of Yangtze River Delta integration, emphasizing housing-price spillover control in core zones, leverage reduction and fiscal resilience in peripheral zones, and strengthened cross-regional coordination.
Qian et al. (Sun,) studied this question.