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Calculation of changes in life expectancy based on proportional hazards model of an intervention

Author

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  • Kulinskaya, Elena
  • Gitsels, Lisanne A.
  • Bakbergenuly, Ilyas
  • Wright, Nigel R.

Abstract

Mortality projections are of great interest to the pension and insurance industry and with an ageing population, the projections need to cover a longer period. A significant question is how to incorporate in mortality projections the longevity risk due to medical advances and uptake of health interventions. We show how hazard ratios obtained from medical studies in combination with the baseline hazards described by Gompertz or Weibull survival distributions, can be translated into changes in individual and population period life expectancy. The impact of medical advances and health interventions can differ among groups of people, such as by sex, age, and deprivation. Changes in life expectancy depend on the composition of the population and these attributes. These calculations are illustrated by a case study on statins, a drug that can significantly improve life expectancy. An R program implementing our methodology is provided in the Appendix.

Suggested Citation

  • Kulinskaya, Elena & Gitsels, Lisanne A. & Bakbergenuly, Ilyas & Wright, Nigel R., 2020. "Calculation of changes in life expectancy based on proportional hazards model of an intervention," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 27-35.
    • Handle: RePEc:eee:insuma:v:93:y:2020:i:c:p:27-35
    DOI: 10.1016/j.insmatheco.2020.04.006
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    References listed on IDEAS

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    1. James W. Vaupel, 2010. "Biodemography of human ageing," Nature, Nature, vol. 464(7288), pages 536-542, March.
    2. Stéphane Loisel, 2010. "Understanding, Modeling and Managing Longevity Risk: Key Issues and Main Challenges," Post-Print hal-00517902, HAL.
    3. Khalaf-Allah, M. & Haberman, S. & Verrall, R., 2006. "Measuring the effect of mortality improvements on the cost of annuities," Insurance: Mathematics and Economics, Elsevier, vol. 39(2), pages 231-249, October.
    4. Devarajan, Karthik & Ebrahimi, Nader, 2011. "A semi-parametric generalization of the Cox proportional hazards regression model: Inference and applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 667-676, January.
    5. Missov, Trifon I. & Lenart, Adam, 2013. "Gompertz–Makeham life expectancies: Expressions and applications," Theoretical Population Biology, Elsevier, vol. 90(C), pages 29-35.
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    Cited by:

    1. Jose A. Valderrama & Javier Olivera, 2023. "The effects of social pensions on mortality among the extreme poor elderly," Documentos de Trabajo / Working Papers 2023-525, Departamento de Economía - Pontificia Universidad Católica del Perú.
    2. Kulinskaya, Elena & Gitsels, Lisanne Andra & Bakbergenuly, Ilyas & Wright, Nigel R., 2021. "Dynamic hazards modelling for predictive longevity risk assessment," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 222-231.

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    More about this item

    Keywords

    Hazard function; Health data; Mortality; Population health; Gompertz distribution; Weibull distribution;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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