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Semi-parametric accelerated hazard relational models with applications to mortality projections

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  • Cadena, Meitner
  • Denuit, Michel

Abstract

In this paper, we propose new relational models linking some specific mortality experience to a reference life table. Compared to existing relational models which distort the forces of mortality, we work here on the age scale. Precisely, age is distorted making individuals younger or older before performing the computations with the reference life table. This is in line with standard actuarial practice, specifically with the so-called Rueff’s adjustments. It is shown that the statistical inference can be conducted with the help of a suitably modified version of the standard IRWLS algorithm in a Poisson GLM/GAM setting. A dynamic version of this model is proposed to produce mortality projections. Numerical illustrations are performed on Belgian mortality statistics.

Suggested Citation

  • Cadena, Meitner & Denuit, Michel, 2016. "Semi-parametric accelerated hazard relational models with applications to mortality projections," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 1-16.
    • Handle: RePEc:eee:insuma:v:68:y:2016:i:c:p:1-16
    DOI: 10.1016/j.insmatheco.2016.02.003
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    Cited by:

    1. Hong Li & Yang Lu, 2018. "A Bayesian non-parametric model for small population mortality," Post-Print hal-02419000, HAL.
    2. Fuino, Michel & Wagner, Joël, 2020. "Duration of long-term care: Socio-economic factors, type of care interactions and evolution," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 151-168.
    3. Cadena, Meitner & Denuit, Michel, 2021. "A new measure of mortality differentials based on precedence probability," LIDAM Discussion Papers ISBA 2021011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

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