Bank Failure Prediction: A Two-Step Survival Time Approach

33 Pages Posted: 24 May 2006

See all articles by Michael Halling

Michael Halling

University of Luxembourg

Evelyn Hayden

Raiffeisen Bank International

Date Written: May 2006

Abstract

In this paper we develop a novel bank failure prediction approach that uses the output of a multiperiod logit model to assess banks' risk situations and then estimates a survival time model for the subset of at-risk ("ill") banks. Our empirical analysis reveals that this two-step approach significantly outperforms benchmark logit models with respect to out-of-sample prediction performance. Furthermore, we identify important differences between the subset of at-risk banks and the entire population of banks regarding the set of significant predictive variables. Management efficiency and size relative to geographically close competitors, for example, are important default predictors for at-risk banks but not for the entire banking population. Consequently, these results have notable policy implications for the design of off-site banking supervision.

Keywords: Default Prediction, Survival Time Analysis, Bank Regulation

JEL Classification: G33, G21, G28, C41

Suggested Citation

Halling, Michael and Hayden, Evelyn, Bank Failure Prediction: A Two-Step Survival Time Approach (May 2006). Available at SSRN: https://ssrn.com/abstract=904255 or http://dx.doi.org/10.2139/ssrn.904255

Michael Halling (Contact Author)

University of Luxembourg ( email )

L-1511 Luxembourg
Luxembourg

Evelyn Hayden

Raiffeisen Bank International ( email )

Am Stadtpark 9
Vienna, A-1030
Austria
+43 1 71707 (Phone)

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