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On age difference in joint lifetime modelling with life insurance annuity applications

Author

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  • Dufresne, François
  • Hashorva, Enkelejd
  • Ratovomirija, Gildas
  • Toukourou, Youssouf

Abstract

Insurance and annuity products covering several lives require the modelling of the joint distribution of future lifetimes. In the interest of simplifying calculations, it is common in practice to assume that the future lifetimes among a group of people are independent. However, extensive research over the past decades suggests otherwise. In this paper, a copula approach is used to model the dependence between lifetimes within a married couple using data from a large Canadian insurance company. As a novelty, the age difference and the gender of the elder partner are introduced as an argument of the dependence parameter. Maximum likelihood techniques are thus implemented for the parameter estimation. Not only do the results make clear that the correlation decreases with age difference, but also the dependence between the lifetimes is higher when husband is older than wife. A goodness-of-fit procedure is applied in order to assess the validity of the model. Finally, considering several annuity products available on the life insurance market, the paper concludes with practical illustrations.

Suggested Citation

  • Dufresne, François & Hashorva, Enkelejd & Ratovomirija, Gildas & Toukourou, Youssouf, 2018. "On age difference in joint lifetime modelling with life insurance annuity applications," Annals of Actuarial Science, Cambridge University Press, vol. 12(2), pages 350-371, September.
    • Handle: RePEc:cup:anacsi:v:12:y:2018:i:02:p:350-371_00
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    Citations

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    Cited by:

    1. Khouzeima Moutanabbir & Hassan Abdelrahman, 2022. "Bivariate Sarmanov Phase-Type Distributions for Joint Lifetimes Modeling," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 1093-1118, June.
    2. Ying Jiao & Yahia Salhi & Shihua Wang, 2021. "Dynamic Bivariate Mortality Modelling," Working Papers hal-03244324, HAL.
    3. Manuel Ventura-Marco & Carlos Vidal-Meliá & Juan Manuel Pérez-Salamero González, 2022. "Life care annuities to help couples cope with the cost of long-term care," Documentos de Trabajo del ICAE 2022-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    4. Gobbi, Fabio & Kolev, Nikolai & Mulinacci, Sabrina, 2021. "Ryu-type extended Marshall-Olkin model with implicit shocks and joint life insurance applications," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 342-358.
    5. Kira Henshaw & Corina Constantinescu & Olivier Menoukeu Pamen, 2020. "Stochastic Mortality Modelling for Dependent Coupled Lives," Risks, MDPI, vol. 8(1), pages 1-28, February.
    6. Deresa, N.W. & Van Keilegom, I. & Antonio, K., 2022. "Copula-based inference for bivariate survival data with left truncation and dependent censoring," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 1-21.
    7. Ying Jiao & Yahia Salhi & Shihua Wang, 2022. "Dynamic Bivariate Mortality Modelling," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 917-938, June.
    8. Ventura-Marco, Manuel & Vidal-Meliá, Carlos & Pérez-Salamero González, Juan Manuel, 2023. "Joint life care annuities to help retired couples to finance the cost of long-term care," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 122-139.

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