Monitoring Banking Sector Fragility: A Multivariate Logit Approach

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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Volume/Issue: Volume 1999 Issue 147
Publication date: October 1999
ISBN: 9781451856712
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Business and Economics , Banks and Banking , Economics- Macroeconomics , WP , crisis probability , banking crisis , banking crises probability , forecasted probability , type I error , Banking crises , bank fragility , monitoring , out-of-sample probability forecast , sample estimation result , Commercial banks , Real interest rates , Systemic crises , East Asia

Summary

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.