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

Alessandro Beretta and Cédric Heuchenne

Journal of Applied Statistics, 2019, vol. 46, issue 9, 1529-1549

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.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:46:y:2019:i:9:p:1529-1549

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DOI: 10.1080/02664763.2018.1554627

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