| Article ID: | iaor2005254 |
| Country: | Netherlands |
| Volume: | 58 |
| Issue: | 3 |
| Start Page Number: | 365 |
| End Page Number: | 380 |
| Publication Date: | Jul 2004 |
| Journal: | Statistica Neerlandica |
| Authors: | Cramer J.S. |
| Keywords: | statistics: regression |
A bank employs logistic regression with state-dependent sample selection to identify loans that may go wrong. The data consist of some 20000 loans for which a number of conventional accounting ratios of the debtor firm are known; after two years just over 600 have gone wrong. Inspection shows that the state-dependent sampling technique does not work because the data do not satisfy the standard logit model. Several variants on this model are considered, and it is found that a bounded logit with a ceiling of (far) less than 1 fits the data better. When it comes to their performance in an independent data-set, however, the differences between the various methods of analysis are negligible.