Sample selection in credit-scoring models

We examine three models for sample selection that are relevant for modeling credit scoring by commercial banks. A binary choice model is used to examine the decision of whether or not to extend credit. The selectivity aspect enters because such models are based on samples of individuals to whom credit has already been given. A regression model with sample selection is suggested for predicting expenditures, or the amount of credit. The same considerations as in the binary choice case apply here. Finally, a model for counts of occurrences is described which could, in some settings also be treated as a model of sample selection. (C) 1998 Elsevier Science B.V.