Dynamic Spatial Treatment Effects and Network Fragility: Theory and Evidence from European Banking
Abstract
This paper develops and empirically implements a continuous functional framework for analyzing systemic risk in financial networks, building on the dynamic spatial treatment effect methodology established in our previous studies. We extend the Navier-Stokes-based approach from our previous studies to characterize contagion dynamics in the European banking system through the spectral properties of network evolution operators. Using high-quality bilateral exposure data from the European Banking Authority Transparency Exercise (2014-2023), we estimate the causal impact of the COVID-19 pandemic on network fragility using spatial difference-in-differences methods adapted from our previous studies. Our empirical analysis reveals that COVID-19 elevated network fragility, measured by the algebraic connectivity $\lambda_2$ of the system Laplacian, by 26.9% above pre-pandemic levels (95% CI: [7.4%, 46.5%], p<0.05), with effects persisting through 2023. Paradoxically, this occurred despite a 46% reduction in the number of banks, demonstrating that consolidation increased systemic vulnerability by intensifying interconnectedness-consistent with theoretical predictions from continuous spatial dynamics. Our findings validate the key predictions from \citet{kikuchi2024dynamical}: treatment effects amplify over time through spatial spillovers, consolidation increases fragility when coupling strength rises, and systems exhibit structural hysteresis preventing automatic reversion to pre-shock equilibria. The results demonstrate the empirical relevance of continuous functional methods for financial stability analysis and provide new insights for macroprudential policy design. We propose network-based capital requirements targeting spectral centrality and stress testing frameworks incorporating diffusion dynamics to address the coupling externalities identified in our analysis.