Home

Competing risks proportional-hazards cure model and generalized extreme value regression: an application to bank failures and acquisitions in the United States

Download Link
Time Added
2022/12/12 19:35
Search
Logistic Regression
Total Downloads
0
Authors
A. Beretta C. Heuchenne and M. Restaino
Abstract
Several commercial banks in the United States disappeared during the last decades due to failure or acquisition by another entity. From a survival analysis perspective however the high censoring rate suggests that some institutions are likely to be immune to failure and/or acquisition. In this study we use a competing risks proportional-hazards cure model in order to measure the impact of bank-specific and macroeconomic variables on the probabilities of being susceptible to these events (i.e. incidence) and on the survival time of susceptible banks (i.e. latency). Moreover we propose to model the incidence distribution using Generalized Extreme Value regression and compare the results with the ones obtained by the usual logistic regression model. The proposed methodology is evaluated by means of a simulation study and then applied to a dataset of more than 4000 United States commercial banks spanning the period 1993–2018.
Keywords
Year Published
2022
Series
Journal of Applied Statistics 2022 vol. 49 issue 16 4162-4180
Rank
0.94
TOP