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Forecasting Bank Failure: A Non-Parametric Frontier Estimation Approach

Published online by Cambridge University Press:  17 August 2016

Richard S. Barr ,
Lawrence M. Seiford  and
Thomas F. Siems
Richard S. Barr
Affiliation:
Southern Methodist University
Lawrence M. Seiford
Affiliation:
University of Massachusetts
Thomas F. Siems
Affiliation:
Federal Reserve Bank of Dallas
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Summary

The dramatic rise in bank failures over the last decade has led to a search for leading indicators so that costly bailouts might be avoided. While the quality of a bank’s management is generally acknowledged to be a key contributor to institutional collapse, it is usually excluded from early-warning models for lack of a metric. This paper describes a new approach for quantifying a bank’s managerial efficiency, using a data-envelopment-analysis model that combines multiple inputs and outputs to compute a scalar measure of efficiency. This new metric captures an elusive, yet crucial, element of institutional success: management quality. New failure-prediction models for detecting a bank’s troubled status which incorporate this explanatory variable have proven to be robust and accurate, as verified by in-depth empirical evaluations, cost sensitivity analyses, and comparisons with other published approaches.

Résumé

Résumé

La très forte augmentation de faillites bancaires au cours de la dernière décennie a mené à la recherche d’indicateurs qui permettraient de prévenir (et éviter) des renflouages coûteux. Alors que la qualité de la gestion des banques est généralement admise comme un facteur clé de ces faillites, elle est le plus souvent exclue des modèles de dépistage précoce par manque de moyens de mesure. Cet article décrit une nouvelle approche permettant de quantifier l’efficacité de la gestion bancaire. Elle utilise un modèle d’analyse dit D.E.A. combinant plusieurs inputs et outputs et fournissant une mesure scalaire de l’efficacité. Cette nouvelle mesure rend compte de cet élément insaisissable, bien que crucial, du succès : la qualité de la gestion. De nouveaux modèles de prédiction de faillites, incorporant cette variable explicative, se sont avérés robustes et précis, comme l’ont montré des analyses et des comparaissons approfondies avec d’autres approches publiées antérieurement.

Keywords

D24D69J21D24D69J21
Type
Research Article
Information
Recherches Économiques de Louvain/ Louvain Economic Review , Volume 60 , Issue 4 , December 1994 , pp. 417 - 429
Copyright
Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 1994 

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Footnotes

(*)

This work was supported in part by National Science Foundation grant DDM-9313346 and the Federal Reserve Bank of Dallas. The opinions expressed herein are those of the authors and do not necessarily reflect those of the National Science Foundation, the Federal Reserve Bank of Dallas, or the Federal Reserve System. The present paper was originally presented at the Third European Workshop on Efficiency and Productivity Measurement, held at CORE, Louvain-La-Neuve, Belgium, October, 1993.

References

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