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A common age effect model for the mortality of multiple populations

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  • Kleinow, Torsten

Abstract

We introduce a model for the mortality rates of multiple populations. To build the proposed model we investigate to what extent a common age effect can be found among the mortality experiences of several countries and use a common principal component analysis to estimate a common age effect in an age–period model for multiple populations. The fit of the proposed model is then compared to age–period models fitted to each country individually, and to the fit of the model proposed by Li and Lee (2005).

Suggested Citation

  • Kleinow, Torsten, 2015. "A common age effect model for the mortality of multiple populations," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 147-152.
  • Handle: RePEc:eee:insuma:v:63:y:2015:i:c:p:147-152
    DOI: 10.1016/j.insmatheco.2015.03.023
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    References listed on IDEAS

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    1. Kleinow, Torsten & Cairns, Andrew J.G., 2013. "Mortality and smoking prevalence: An empirical investigation in ten developed countries," British Actuarial Journal, Cambridge University Press, vol. 18(2), pages 452-466, July.
    2. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    3. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
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    Cited by:

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    2. Qian Lu & Katja Hanewald & Xiaojun Wang, 2021. "Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors," Risks, MDPI, vol. 9(11), pages 1-21, November.
    3. Snorre Jallbjørn & Søren Fiig Jarner, 2022. "Sex Differential Dynamics in Coherent Mortality Models," Forecasting, MDPI, vol. 4(4), pages 1-26, September.
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    5. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    6. Bruszas, Sandy & Kaschützke, Barbara & Maurer, Raimond & Siegelin, Ivonne, 2018. "Unisex pricing of German participating life annuities—Boon or bane for customer and insurance company?," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 230-245.
    7. Blake, David & El Karoui, Nicole & Loisel, Stéphane & MacMinn, Richard, 2018. "Longevity risk and capital markets: The 2015–16 update," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 157-173.
    8. McCarthy, David G. & Wang, Po-Lin, 2021. "Pooling mortality risk in Eurozone state pension liabilities: An application of a Bayesian coherent multi-population cohort-based mortality model," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 459-485.
    9. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2022. "Thirty years on: A review of the Lee-Carter method for forecasting mortality," SocArXiv 8u34d, Center for Open Science.
    10. Bozikas, Apostolos & Pitselis, Georgios, 2020. "Incorporating crossed classification credibility into the Lee–Carter model for multi-population mortality data," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 353-368.
    11. Massimiliano Menzietti & Maria Francesca Morabito & Manuela Stranges, 2019. "Mortality Projections for Small Populations: An Application to the Maltese Elderly," Risks, MDPI, vol. 7(2), pages 1-25, March.
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    13. Nhan Huynh & Mike Ludkovski, 2021. "Joint Models for Cause-of-Death Mortality in Multiple Populations," Papers 2111.06631, arXiv.org.
    14. Li, Johnny Siu-Hang & Liu, Yanxin, 2020. "The heat wave model for constructing two-dimensional mortality improvement scales with measures of uncertainty," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 1-26.
    15. Andrew J.G. Cairns & Malene Kallestrup-Lamb & Carsten P.T. Rosenskjold & David Blake & Kevin Dowd, 2016. "Modelling Socio-Economic Differences in the Mortality of Danish Males Using a New Affluence Index," CREATES Research Papers 2016-14, Department of Economics and Business Economics, Aarhus University.
    16. Jackie Li & Leonie Tickle & Nick Parr, 2016. "A multi-population evaluation of the Poisson common factor model for projecting mortality jointly for both sexes," Journal of Population Research, Springer, vol. 33(4), pages 333-360, December.
    17. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    18. Wang, Pengjie & Pantelous, Athanasios A. & Vahid, Farshid, 2023. "Multi-population mortality projection: The augmented common factor model with structural breaks," International Journal of Forecasting, Elsevier, vol. 39(1), pages 450-469.
    19. Francesca Perla & Salvatore Scognamiglio, 2023. "Locally-coherent multi-population mortality modelling via neural networks," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 46(1), pages 157-176, June.
    20. Kenneth Wong & Jackie Li & Sixian Tang, 2020. "A modified common factor model for modelling mortality jointly for both sexes," Journal of Population Research, Springer, vol. 37(2), pages 181-212, June.
    21. Jarner, Søren F. & Jallbjørn, Snorre, 2020. "Pitfalls and merits of cointegration-based mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 80-93.
    22. Hanbali, Hamza & Dhaene, Jan & Linders, Daniël, 2022. "Dependence bounds for the difference of stop-loss payoffs on the difference of two random variables," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 22-37.
    23. Li, Hong & Shi, Yanlin, 2021. "Forecasting mortality with international linkages: A global vector-autoregression approach," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 59-75.

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