Submitted:
23 July 2018
Posted:
23 July 2018
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Abstract
In this paper, we use the Principal Components Logistic Regression as a technique to reduce the variables being used in Credit Scoring Modeling. Specifically, we construct two models in which greek enterprises are classified, through their credit behavior and we evaluate them, relying on real data. In general, we propose a general way to use PC Regression, in case that we have high correlations and categorical variables in the sample.
Keywords:
P.C. regression
; AIC criterion
; logit function
; pearson's Chi-square use
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