Name
Abstract | ||
|---|---|---|
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 presents 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 and quality. An analysis of 930 banks over a five-year period shows significant differences in management-quality scores between surviving and failing institutions. These differences are detectable long before failure occurs and increase as the failure date approaches. Hence this new metric provides an important, yet previously missing, modelling element for the early identification of troubled banks. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1007/BF02282039 | Annals OR |
Keywords | Field | DocType |
Modelling Element,Early Warning,Early Identification,Scalar Measure,Managerial Efficiency | Warning system,Actuarial science,Scalar (physics),Economic indicator,Envelopment,Mathematics | Journal |
Volume | Issue | Citations |
45 | 1-4 | 17 |
PageRank | References | Authors |
6.02 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Richard S. Barr | 1 | 255 | 28.84 |
| Lawrence M. Seiford | 2 | 552 | 51.63 |
| Thomas F. Siems | 3 | 17 | 6.02 |