This article explores how a multivariate logit model of the probability of a banking crisis can be used to monitor banking sector fragility. The proposed approach relies on readily available data, and the fragility assessment has a clear interpretation based on in-sample statistics. The model has better in-sample performance than currently available alternatives, and the monitoring system can be tailored to fit the preferences of decisionmakers regarding type I and type II errors. The framework can be useful as a preliminary screen to economize on precautionary costs.
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Demirgüç‐Kunt et al. (2000) studied this question.