A hierarchical mixture cure model with unobserved heterogeneity for credit risk
نویسندگان
چکیده
The specific nature of credit loan data requires the use mixture cure models within class survival analysis tools. constructed allow for competing risks such as early repayment and default, incorporating maturity, expressed an unsusceptible part population. A novel further extension incorporates unobserved heterogeneity risk groups. hierarchical expectation-maximization algorithm is derived to fit standard errors are obtained. Simulations a illustrate applicability benefits these models, in particular improved event time estimation.
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ژورنال
عنوان ژورنال: Econometrics and Statistics
سال: 2022
ISSN: ['2452-3062', '2468-0389']
DOI: https://doi.org/10.1016/j.ecosta.2020.12.002