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Variable selection in proportional hazards cure model with time-varying covariates, application to US bank failures

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  • Alessandro Beretta
  • Cédric Heuchenne

Abstract

From a survival analysis perspective, bank failure data are often characterized by small default rates and heavy censoring. This empirical evidence can be explained by the existence of a subpopulation of banks likely immune from bankruptcy. In this regard, we use a mixture cure model to separate the factors with an influence on the susceptibility to default from the ones affecting the survival time of susceptible banks. In this paper, we extend a semi-parametric proportional hazards cure model to time-varying covariates and we propose a variable selection technique based on its penalized likelihood. By means of a simulation study, we show how this technique performs reasonably well. Finally, we illustrate an application to commercial bank failures in the United States over the period 2006–2016.

Suggested Citation

  • Alessandro Beretta & Cédric Heuchenne, 2019. "Variable selection in proportional hazards cure model with time-varying covariates, application to US bank failures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(9), pages 1529-1549, July.
    • Handle: RePEc:taf:japsta:v:46:y:2019:i:9:p:1529-1549
    DOI: 10.1080/02664763.2018.1554627
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    Cited by:

    1. Ana López-Cheda & Yingwei Peng & María Amalia Jácome, 2023. "Nonparametric estimation in mixture cure models with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 467-495, June.

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