We investigate the accuracy of the Z-score, a widely used proxy of bank soundness, on a sample of European banks from 12 countries over the period 2001–2011. Specifically, we run a horse race analysis between the Z-score and the CAMELS related covariates. Using probit and complementary log–log models, we find that the Z-score's ability to identify distress events, both in the whole period and during the crisis years (2008–2011), is at least as good as the CAMELS variables, but with the advantage of being less data demanding. Finally, the Z-score proves to be more effective when bank business models may be more sophisticated as it is the case for large and commercial banks.
Should we trust the Z-score? Evidence from the European banking industry
Chiaramonte, L.;
2015-01-01
Abstract
We investigate the accuracy of the Z-score, a widely used proxy of bank soundness, on a sample of European banks from 12 countries over the period 2001–2011. Specifically, we run a horse race analysis between the Z-score and the CAMELS related covariates. Using probit and complementary log–log models, we find that the Z-score's ability to identify distress events, both in the whole period and during the crisis years (2008–2011), is at least as good as the CAMELS variables, but with the advantage of being less data demanding. Finally, the Z-score proves to be more effective when bank business models may be more sophisticated as it is the case for large and commercial banks.
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