Corporate Default Prediction with Industry Effects: Evidence from Emerging Markets
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 pre...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EconJournals
2016-06-01
|
| Series: | International Journal of Economics and Financial Issues |
| Online Access: | https://www.econjournals.com/index.php/ijefi/article/view/2625 |
| Summary: | 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
|
|---|---|
| ISSN: | 2146-4138 |