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Lifetime dependence modelling using a truncated multivariate gamma distribution

Author

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  • Alai, Daniel H.
  • Landsman, Zinoviy
  • Sherris, Michael

Abstract

Systematic improvements in mortality increases dependence in the survival distributions of insured lives, which is not accounted for in standard life tables and actuarial models used for annuity pricing and reserving. Systematic longevity risk also undermines the law of large numbers, a law that is relied on in the risk management of life insurance and annuity portfolios. This paper applies a multivariate gamma distribution to incorporate dependence. Lifetimes are modelled using a truncated multivariate gamma distribution that induces dependence through a shared gamma distributed component. Model parameter estimation is developed based on the method of moments and generalized to allow for truncated observations. The impact of dependence within a portfolio, or cohort, of lives with similar risk characteristics is demonstrated by applying the model to annuity valuation. Dependence is shown to have a significant impact on the risk of the annuity portfolio as compared with traditional actuarial methods that implicitly assume independent lifetimes.

Suggested Citation

  • Alai, Daniel H. & Landsman, Zinoviy & Sherris, Michael, 2013. "Lifetime dependence modelling using a truncated multivariate gamma distribution," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 542-549.
    • Handle: RePEc:eee:insuma:v:52:y:2013:i:3:p:542-549
    DOI: 10.1016/j.insmatheco.2013.03.011
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    References listed on IDEAS

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    1. Mathai, A. M. & Moschopoulos, P. G., 1991. "On a multivariate gamma," Journal of Multivariate Analysis, Elsevier, vol. 39(1), pages 135-153, October.
    2. Denuit, Michel, 2008. "Comonotonic approximations to quantiles of life annuity conditional expected present value," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 831-838, April.
    3. Varadhan, Ravi & Gilbert, Paul, 2009. "BB: An R Package for Solving a Large System of Nonlinear Equations and for Optimizing a High-Dimensional Nonlinear Objective Function," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i04).
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    Citations

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    Cited by:

    1. Zhou, Ming & Dhaene, Jan & Yao, Jing, 2018. "An approximation method for risk aggregations and capital allocation rules based on additive risk factor models," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 92-100.
    2. Denuit, Michel & Lu, Yang, 2020. "Wishart-Gamma mixtures for multiperil experience ratemaking, frequency-severity experience rating and micro-loss reserving," LIDAM Discussion Papers ISBA 2020016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Michel Denuit & Yang Lu, 2021. "Wishart‐gamma random effects models with applications to nonlife insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(2), pages 443-481, June.
    4. Alai, Daniel H. & Landsman, Zinoviy & Sherris, Michael, 2016. "Modelling lifetime dependence for older ages using a multivariate Pareto distribution," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 272-285.
    5. Martín Egozcue & Jiang Wu & Ričardas Zitikis, 2017. "Optimal two-stage pricing strategies from the seller’s perspective under the uncertainty of buyer’s decisions," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-25, December.
    6. Furman, Edward & Kuznetsov, Alexey & Zitikis, Ričardas, 2018. "Weighted risk capital allocations in the presence of systematic risk," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 75-81.
    7. Alai, Daniel H. & Landsman, Zinoviy & Sherris, Michael, 2015. "A multivariate Tweedie lifetime model: Censoring and truncation," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 203-213.

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    More about this item

    Keywords

    Systematic longevity risk; Dependence; Multivariate gamma; Lifetime distribution; Annuity valuation;
    All these keywords.

    JEL classification:

    • 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
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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