Latent Fragility and Clustered Withdrawals in Dynamic Banks Runs

2026-07-24

AI Summary

This study addresses why bank runs exhibit clustered withdrawal patterns despite gradual and heterogeneous shocks. Building on a mean-field game framework, the paper develops a dynamic bank-run model that introduces a “latent fragility” mechanism: run-prone depositors accumulate over time, and although each individual prefers to wait, a self-fulfilling expectation of collective withdrawal triggers synchronized runs. This mechanism endogenously generates clustering behavior under both discrete and continuous heterogeneity and characterizes equilibrium structures—including earliest, latest, and unique threshold equilibria. Through dynamic equilibrium analysis and threshold-strategy modeling, the paper establishes equilibrium existence and demonstrates how a common macroeconomic state variable coordinates individual decisions, successfully replicating the clustered withdrawal patterns observed in real-world bank runs.

Abstract

Using a mean-field game framework, we study a dynamic model of bank runs in which more withdrawals raise the risk of bank failure. Even though depositors receive gradual and idiosyncratic shocks, withdrawals occur in clusters. The main mechanism is latent fragility: run-prone depositors accumulate gradually over time and may prefer to wait individually, but they withdraw together once collective exit becomes self-fulfilling. We establish equilibrium existence and characterize earliest-run and latest-run equilibria. The clustering mechanism arises whether depositor heterogeneity is discrete or continuous. A common aggregate state coordinates withdrawal timing and leads to a unique threshold equilibrium.

Problem

• bank runs
• latent fragility
• clustered withdrawals
• mean-field game
• equilibrium

Innovation

• mean-field game
• latent fragility
• bank runs
• clustered withdrawals
• threshold equilibrium