This paper explores how a multivariate logit empirical model of banking crisis probabilities 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 the decision maker 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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