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.
|Titolo:||Business Failure Prediction in Manufacturing: A Robust Bayesian Approach to Discriminant Scoring|
|Data di pubblicazione:||2014|
|Appare nelle tipologie:||2.1 Contributo in volume(Capitolo di libro)|