Corporate Default Prediction with Industry Effects: Evidence from Emerging Markets

Yıl 2016, Cilt: 6 Sayı: 3, 161 - 169, 01.05.2016

Maryam Mirzaei Suresh Ramakrishnan Mahmoud Bekri

Öz

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.

Anahtar Kelimeler

Default prediction modelling, Industry effects, Emerging markets