This paper provides a methodological analysis of credit risk in manufacturing firms. By using a representative sample of both healthy and bankrupted firms during the period 2003–2009 we provide an in-depth comparison of the standard discriminant approach for bankruptcy prediction based on a logistic regression model and a Robust Bayesian Approach. We conclude that the use of a robust GLM regression methodology enables us to provide a more accurate separation between sound and unsound firms thus suggesting that this methodological framework may be used to achieve a more reliable measure of firms credit worthiness.
|Title of host publication||Advances in Latent Variables|
|Editors||Maurizio, Eugenio Brentari, and E. M. Qannari. Carpita|
|Number of pages||9|
|Publication status||Published - 2015|
- Discriminant analysis
- Forward search
- Robust GLM regression