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.
Original language | English |
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Pages (from-to) | 40-53 |
Number of pages | 14 |
Journal | Journal of Business and Economic Statistics |
Volume | 37 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2 Jan 2019 |
Externally published | Yes |
Keywords
- Credit risk modeling
- Macro-economic factors
- Mixture cure model
- Survival analysis
- Time-varying covariates
ASJC Scopus subject areas
- Statistics and Probability
- Social Sciences (miscellaneous)
- Economics and Econometrics
- Statistics, Probability and Uncertainty