Abstract
The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is because default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modeled, distinct from time of default for the susceptible population. In this article, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank dataset.
Acknowledgments
The authors thank all reviewers of this article for their helpful suggestions and comments. The authors acknowledge the support of the Fund for Scientific Research Flanders, KU Leuven grant GOA/12/14 and of the IAP Research Network P7/06 of the Belgian Science Policy. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Hercules Foundation and the Flemish Government – department EWI.