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Parametric Bootstrap Estimation of Standard Errors in Survival Models When Covariates are Missing

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Francesco Ungolo

    (Technische Universität München)

  • Torsten Kleinow

    (Heriot-Watt University and Maxwell Institute of Mathematical Sciences)

  • Angus S. Macdonald

    (Heriot-Watt University and Maxwell Institute of Mathematical Sciences)

Abstract

We propose and analyze parametric bootstrapping for estimating the standard error of the parameter estimates of regression models for the mortality hazard function, in a survival model when covariates on individual lives are missing at random. Using an example based on UK pension scheme members, we describe the methodology and its impact on the mis-estimation risk capital requirement.

Suggested Citation

  • Francesco Ungolo & Torsten Kleinow & Angus S. Macdonald, 2021. "Parametric Bootstrap Estimation of Standard Errors in Survival Models When Covariates are Missing," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 389-394, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-78965-7_57
    DOI: 10.1007/978-3-030-78965-7_57
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