文章基本信息

标题：Corporate Default Prediction with Industry Effects: Evidence from Emerging Markets
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作者：Maryam Mirzaei ; Suresh Ramakrishnan ; Mahmoud Bekri 等
期刊名称：International Journal of Economics and Financial Issues
电子版ISSN：2146-4138
出版年度：2016
卷号：6
期号：3S
页码：161-169
语种：English
出版社：EconJournals
摘要：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
其他摘要：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