Corporate Default Prediction with Industry Effects: Evidence from Emerging Markets

Authors

  • Maryam Mirzaei
  • Suresh Ramakrishnan
  • Mahmoud Bekri

Abstract

The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors. Firm-specific data accompany with industry and macroeconomic factors offer a potentially large number of candidate predictors of corporate default. We employ a predictor selection procedure based on non-parametric regression and classification tree method (CART) and test its performance within a standard logistic regression model. Overall entire analyses indicate that the orientation between firm-level determinants and the probability of default is affected by each industry's characteristics. As well, our selection method represents an efficient way of introducing non-linear effects of predictor variables on the default probability.

Keywords: Default prediction modelling; Industry effects; Emerging markets

JEL Classification: E00 

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Published

2016-06-12

How to Cite

Mirzaei, M., Ramakrishnan, S., & Bekri, M. (2016). Corporate Default Prediction with Industry Effects: Evidence from Emerging Markets. International Journal of Economics and Financial Issues, 6(3S), 161–169. Retrieved from https://www.econjournals.com/index.php/ijefi/article/view/2625