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Variable selection in proportional hazards cure model with time-varying covariates, application to US bank failures
Beretta, Alessandro
2018
 

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Keywords :
bank failures; survival analysis; mixture cure model; time-varying covariates; penalized likelihood; SCAD
Abstract :
[en] From a survival analysis perspective, bank failure data are often characterised 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. We extend a semi-parametric proportional hazards cure model to time-varying covariates and we propose a penalized-likelihood variable selection technique. 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.
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Beretta, Alessandro ;  Université de Liège - ULiège > HEC Liège : UER > UER Opérations
Language :
English
Title :
Variable selection in proportional hazards cure model with time-varying covariates, application to US bank failures
Publication date :
22 May 2018
Event name :
Seminar at University of Salerno
Event place :
Salerno, Italy
Event date :
22-05-2018
Available on ORBi :
since 12 June 2018

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