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Dependence Modelling of Lifetimes in Egyptian Families

Author

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  • Kira Henshaw

    (Department of Mathematical Sciences, Institute for Financial and Actuarial Mathematics, University of Liverpool, Liverpool L69 7ZL, UK)

  • Waleed Hana

    (Department of Insurance and Actuarial Science, Cairo University, Cairo 12613, Egypt)

  • Corina Constantinescu

    (Department of Mathematical Sciences, Institute for Financial and Actuarial Mathematics, University of Liverpool, Liverpool L69 7ZL, UK)

  • Dalia Khalil

    (Department of Insurance and Actuarial Science, Cairo University, Cairo 12613, Egypt)

Abstract

In this study, we analyse a large sample of Egyptian social pension data which covers, by law, the policyholder’s spouse, children, parents and siblings. This data set uniquely enables the study and comparison of pairwise dependence between multiple familial relationships beyond the well-known husband and wife case. Applying Bayesian Markov Chain Monte Carlo (MCMC) estimation techniques with the two-step inference functions for margins (IFM) method, we model dependence between lifetimes in spousal, parent–child and child–parent relationships, using copulas to capture the strength of association. Dependence is observed to be strongest in child–parent relationships and, in comparison to the high-income countries of data sets previously studied, of lesser significance in the husband and wife case, often referred to as broken-heart syndrome. Given the traditional use of UK mortality tables in the modelling of mortality in Egypt, the findings of this paper will help to inform appropriate mortality assumptions specific to the unique structure of the Egyptian scheme.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jrisks:v:11:y:2023:i:1:p:18-:d:1032194
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    References listed on IDEAS

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    1. Gerard J. van den Berg & Bettina Drepper, 2022. "A unique bond: Twin bereavement and lifespan associations of identical and fraternal twins," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(2), pages 677-698, April.
    2. van den Berg, Gerard J. & Drepper, Bettina, 2018. "A Unique Bond: Twin Bereavement and Lifespan Associations of Identical and Fraternal Twins," IZA Discussion Papers 11448, Institute of Labor Economics (IZA).
    3. Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
    4. Andrew Cairns & David Blake & Kevin Dowd & Guy Coughlan & David Epstein & Alen Ong & Igor Balevich, 2009. "A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(1), pages 1-35.
    5. Spreeuw, Jaap & Owadally, Iqbal, 2013. "Investigating the Broken-Heart Effect: a Model for Short-Term Dependence between the Remaining Lifetimes of Joint Lives," Annals of Actuarial Science, Cambridge University Press, vol. 7(2), pages 236-257, September.
    6. Ioannis Ntzoufras & Petros Dellaportas, 2002. "Bayesian Modelling of Outstanding Liabilities Incorporating Claim Count Uncertainty," North American Actuarial Journal, Taylor & Francis Journals, vol. 6(1), pages 113-125.
    7. Elizabeth Zenger, 1993. "Siblings’ neonatal mortality risks and birth spacing in Bangladesh," Demography, Springer;Population Association of America (PAA), vol. 30(3), pages 477-488, August.
    8. Luciano, Elisa & Spreeuw, Jaap & Vigna, Elena, 2008. "Modelling stochastic mortality for dependent lives," Insurance: Mathematics and Economics, Elsevier, vol. 43(2), pages 234-244, October.
    9. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    10. Booth, H. & Tickle, L., 2008. "Mortality Modelling and Forecasting: a Review of Methods," Annals of Actuarial Science, Cambridge University Press, vol. 3(1-2), pages 3-43, September.
    11. LUCIANO, Elisa & VIGNA, Elena, 2008. "Mortality risk via affine stochastic intensities: calibration and empirical relevance," MPRA Paper 59627, University Library of Munich, Germany.
    12. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485564, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
    13. Brechmann, Eike C. & Hendrich, Katharina & Czado, Claudia, 2013. "Conditional copula simulation for systemic risk stress testing," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 722-732.
    14. Silva Filho, Osvaldo Candido da & Ziegelmann, Flavio Augusto & Dueker, Michael J., 2012. "Modeling dependence dynamics through copulas with regime switching," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 346-356.
    15. Cairns, Andrew J.G. & Blake, David & Dowd, Kevin & Coughlan, Guy D. & Khalaf-Allah, Marwa, 2011. "Bayesian Stochastic Mortality Modelling for Two Populations," ASTIN Bulletin, Cambridge University Press, vol. 41(1), pages 29-59, May.
    16. Biffis, Enrico, 2005. "Affine processes for dynamic mortality and actuarial valuations," Insurance: Mathematics and Economics, Elsevier, vol. 37(3), pages 443-468, December.
    17. Almeida, Carlos & Czado, Claudia, 2012. "Efficient Bayesian inference for stochastic time-varying copula models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1511-1527.
    18. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718, December.
    19. Huard, David & Evin, Guillaume & Favre, Anne-Catherine, 2006. "Bayesian copula selection," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 809-822, November.
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