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Corporate Default Prediction with Industry Effects : Evidence from Emerging Markets

Mirzaei, Maryam; Ramakrishnan, Suresh; Bekri, Mahmoud

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.

Zugehörige Institution(en) am KIT Fakultät für Wirtschaftswissenschaften (WIWI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2016
Sprache Englisch
Identifikator ISSN: 2146-4138
URN: urn:nbn:de:swb:90-559823
KITopen ID: 1000055982
Erschienen in International Journal of Economics and Financial Issues
Band 6
Heft S3
Seiten 161-169
Lizenz CC BY 4.0: Creative Commons Namensnennung 4.0 International
Schlagworte Default Prediction Modeling, Industry Effects, Emerging Markets
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