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Modeling Joint Lives within Families

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Abstract

Family history is usually seen as a significant factor insurance companies look at when applying for a life insurance policy. Where it is used, family history of cardiovascular diseases, death by cancer, or family history of high blood pressure and diabetes could result in higher premiums or no coverage at all. In this article, we use massive (historical) data to study dependencies between life length within families. If joint life contracts (between a husband and a wife) have been long studied in actuarial literature, little is known about child and parents dependencies. We illustrate those dependencies using 19th century family trees in France, and quantify implications in annuities computations. For parents and children, we observe a modest but significant positive association between life lengths. It yields different estimates for remaining life expectancy, present values of annuities, or whole life insurance guarantee, given information about the parents (such as the number of parents alive). A similar but weaker pattern is observed when using information on grandparents.

Suggested Citation

  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
    • Handle: RePEc:aim:wpaimx:2021
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    References listed on IDEAS

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    1. David M. Cutler & Richard J. Zeckhauser, 1998. "Adverse Selection in Health Insurance," NBER Chapters, in: Frontiers in Health Policy Research, Volume 1, pages 1-32, National Bureau of Economic Research, Inc.
    2. Gery Geenens & Arthur Charpentier & Davy Paindaveine, 2014. "Probit Transformation for Nonparametric Kernel Estimation of the Copula Density," Working Papers ECARES ECARES 2014-23, ULB -- Universite Libre de Bruxelles.
    3. Olivier Scaillet, 2005. "A Kolmogorov-Smirnov Type Test for Positive Quadrant Dependence," FAME Research Paper Series rp128, International Center for Financial Asset Management and Engineering.
    4. Spedicato, Giorgio Alfredo, 2013. "The lifecontingencies Package: Performing Financial and Actuarial Mathematics Calculations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 55(i10).
    5. James Vaupel, 1988. "Inherited frailty and longevity," Demography, Springer;Population Association of America (PAA), vol. 25(2), pages 277-287, May.
    6. Patrizio Piraino & Sean Muller & Jeanne Cilliers & Johan Fourie, 2013. "The transmission of longevity across generations: The case of the settler Cape Colony," Working Papers 14/2013, Stellenbosch University, Department of Economics.
    7. Espinosa, Javier & Evans, William N., 2008. "Heightened mortality after the death of a spouse: Marriage protection or marriage selection?," Journal of Health Economics, Elsevier, vol. 27(5), pages 1326-1342, September.
    8. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    9. Michel Denuit, 2004. "Nonparametric Tests for Positive Quadrant Dependence," Journal of Financial Econometrics, Oxford University Press, vol. 2(3), pages 422-450.
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    Cited by:

    1. Kira Henshaw & Waleed Hana & Corina Constantinescu & Dalia Khalil, 2023. "Dependence Modelling of Lifetimes in Egyptian Families," Risks, MDPI, vol. 11(1), pages 1-25, January.
    2. Arthur Charpentier & Lariosse Kouakou & Matthias Lowe & Philipp Ratz & Franck Vermet, 2021. "Collaborative Insurance Sustainability and Network Structure," Papers 2107.02764, arXiv.org, revised Sep 2022.

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    More about this item

    Keywords

    annuities; collaborative data; dependence; family history; genealogy; grandparents-grandchildren; information; joint life insurance; parents-children; whole life insurance;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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