IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v91y2020icp37-54.html
   My bibliography  Save this article

Incorporating hierarchical credibility theory into modelling of multi-country mortality rates

Author

Listed:
  • Tsai, Cary Chi-Liang
  • Wu, Adelaide Di

Abstract

A hierarchical credibility model is a generalization of the Bühlmann credibility model and the Bühlmann–Straub credibility model with a tree structure of four or more levels. This paper aims to incorporate hierarchical credibility theory, which is used in property and casualty insurance, to model multi-country mortality rates. The forecasting performances of the three/four/five-level hierarchical credibility models are compared with those of the classical Lee–Carter model and its three extensions for multiple populations (the joint- k, the co-integrated, and the augmented common factor Lee–Carter models). Numerical illustrations based on mortality data from the Human Mortality Database for both genders of the US, the UK and Japan with a series of fitting year spans and three forecasting periods show that the hierarchical credibility approach contributes to more accurate forecasts measured by the AMAPE (average of mean absolute percentage errors). Finally, a stochastic version of the proposed hierarchical credibility mortality model is also proposed, which can be used to construct predictive intervals on the projected mortality rates and to conduct stochastic simulations for applications.

Suggested Citation

  • Tsai, Cary Chi-Liang & Wu, Adelaide Di, 2020. "Incorporating hierarchical credibility theory into modelling of multi-country mortality rates," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 37-54.
    • Handle: RePEc:eee:insuma:v:91:y:2020:i:c:p:37-54
    DOI: 10.1016/j.insmatheco.2020.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167668720300019
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.insmatheco.2020.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Hua & MacMinn, Richard & Sun, Tao, 2015. "Multi-population mortality models: A factor copula approach," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 135-146.
    2. 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.
    3. Johnny Siu-Hang Li & Wai-Sum Chan & Rui Zhou, 2017. "Semicoherent Multipopulation Mortality Modeling: The Impact on Longevity Risk Securitization," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(3), pages 1025-1065, September.
    4. Wang, Chou-Wen & Yang, Sharon S. & Huang, Hong-Chih, 2015. "Modeling multi-country mortality dependence and its application in pricing survivor index swaps—A dynamic copula approach," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 30-39.
    5. 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.
    6. Cary Chi-Liang Tsai & Tzuling Lin, 2017. "A Bühlmann Credibility Approach to Modeling Mortality Rates," North American Actuarial Journal, Taylor & Francis Journals, vol. 21(2), pages 204-227, April.
    7. 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.
    8. Cary Chi-Liang Tsai & Shuai Yang, 2015. "A Linear Regression Approach to Modeling Mortality Rates of Different Forms," North American Actuarial Journal, Taylor & Francis Journals, vol. 19(1), pages 1-23, January.
    9. Lin, Tzuling & Wang, Chou-Wen & Tsai, Cary Chi-Liang, 2015. "Age-specific copula-AR-GARCH mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 110-124.
    10. Wang, Zihe & Li, Johnny Siu-Hang, 2016. "A DCC-GARCH multi-population mortality model and its applications to pricing catastrophic mortality bonds," Finance Research Letters, Elsevier, vol. 16(C), pages 103-111.
    11. 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.
    12. Li, Johnny Siu-Hang & Zhou, Rui & Hardy, Mary, 2015. "A step-by-step guide to building two-population stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 121-134.
    13. Johnny Li & Mary Hardy, 2011. "Measuring Basis Risk in Longevity Hedges," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(2), pages 177-200.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei Wang & Limin Wen & Zhixin Yang & Quan Yuan, 2020. "Quantile Credibility Models with Common Effects," Risks, MDPI, vol. 8(4), pages 1-10, September.
    2. 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.
    3. Hung-Tsung Hsiao & Chou-Wen Wang & I.-Chien Liu & Ko-Lun Kung, 2024. "Mortality improvement neural-network models with autoregressive effects," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 363-383, April.
    4. Salazar García, Juan Fernando & Guzmán Aguilar, Diana Sirley & Hoyos Nieto, Daniel Arturo, 2023. "Modelación de una prima de seguros mediante la aplicación de métodos actuariales, teoría de fallas y Black-Scholes en la salud en Colombia [Modelling of an insurance premium through the application," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 35(1), pages 330-359, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Zhou, Rui & Ji, Min, 2021. "Modelling mortality dependence: An application of dynamic vine copula," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 241-255.
    3. Hung-Tsung Hsiao & Chou-Wen Wang & I.-Chien Liu & Ko-Lun Kung, 2024. "Mortality improvement neural-network models with autoregressive effects," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 363-383, April.
    4. 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.
    5. 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.
    6. Simon Schnürch & Torsten Kleinow & Ralf Korn, 2021. "Clustering-Based Extensions of the Common Age Effect Multi-Population Mortality Model," Risks, MDPI, vol. 9(3), pages 1-32, March.
    7. 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.
    8. Yang Qiao & Chou-Wen Wang & Wenjun Zhu, 2024. "Machine learning in long-term mortality forecasting," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 340-362, April.
    9. 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.
    10. Selin Özen & Şule Şahin, 2021. "A Two-Population Mortality Model to Assess Longevity Basis Risk," Risks, MDPI, vol. 9(2), pages 1-19, February.
    11. Bravo, Jorge M. & Ayuso, Mercedes & Holzmann, Robert & Palmer, Edward, 2021. "Addressing the life expectancy gap in pension policy," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 200-221.
    12. Hunt, Andrew & Blake, David, 2015. "Modelling longevity bonds: Analysing the Swiss Re Kortis bond," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 12-29.
    13. Li, Hong & Lu, Yang, 2017. "Coherent Forecasting Of Mortality Rates: A Sparse Vector-Autoregression Approach," ASTIN Bulletin, Cambridge University Press, vol. 47(2), pages 563-600, May.
    14. Norkhairunnisa Redzwan & Rozita Ramli, 2022. "A Bibliometric Analysis of Research on Stochastic Mortality Modelling and Forecasting," Risks, MDPI, vol. 10(10), pages 1-17, October.
    15. Guibert, Quentin & Lopez, Olivier & Piette, Pierrick, 2019. "Forecasting mortality rate improvements with a high-dimensional VAR," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 255-272.
    16. Uditha Balasooriya & Johnny Siu-Hang Li & Jackie Li, 2020. "The Impact of Model Uncertainty on Index-Based Longevity Hedging and Measurement of Longevity Basis Risk," Risks, MDPI, vol. 8(3), pages 1-27, August.
    17. Selin Ozen & c{S}ule c{S}ahin, 2021. "A Two-Population Mortality Model to Assess Longevity Basis Risk," Papers 2101.06690, arXiv.org.
    18. Cairns, Andrew J.G., 2011. "Modelling and management of longevity risk: Approximations to survivor functions and dynamic hedging," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 438-453.
    19. Li, Johnny Siu-Hang & Liu, Yanxin & Chan, Wai-Sum, 2023. "Hedging longevity risk under non-Gaussian state-space stochastic mortality models: A mean-variance-skewness-kurtosis approach," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 96-121.
    20. Ahmadi, Seyed Saeed & Li, Johnny Siu-Hang, 2014. "Coherent mortality forecasting with generalized linear models: A modified time-transformation approach," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 194-221.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:insuma:v:91:y:2020:i:c:p:37-54. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.