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

Author

Listed:
  • Beretta, Alessandro
  • Heuchenne, Cédric

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Restaino, Marialuisa

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.

Suggested Citation

  • Beretta, Alessandro & Heuchenne, Cédric & Restaino, Marialuisa, 2021. "Competing risks proportional-hazards cure model and generalized extreme value regression: an application to bank failures and acquisitions in the United States," LIDAM Reprints ISBA 2021035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2021035
    DOI: https://doi.org/10.1080/02664763.2021.1973386
    Note: In: Journal of Applied Statistics, 2021
    as

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