Business failure prediction in manufacturing: A robust bayesian approach to discriminant scoring

Maurizio Luigi Baussola, Aldo Corbellini, Eleonora Bartoloni

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.
Original languageEnglish
Title of host publicationAdvances in Latent Variables
EditorsMaurizio, Eugenio Brentari, and E. M. Qannari. Carpita
Pages277-285
Number of pages9
DOIs
Publication statusPublished - 2015

Keywords

  • Bankruptcy
  • Discriminant analysis
  • Forward search
  • Robust GLM regression

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