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A General Procedure for Constructing Mortality Models

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  • Andrew Hunt
  • David Blake

Abstract

Recently a large number of new mortality models have been proposed to analyze historic mortality rates and project them into the future. Many of these suffer from being over-parametrized or have terms added in an ad hoc manner that cannot be justified in terms of demographic significance. In addition, poor specification of a model can lead to period effects in the data being wrongly attributed to cohort effects, which results in the model making implausible projections. We present a general procedure for constructing mortality models using a combination of a toolkit of functions and expert judgment. By following the general procedure, it is possible to identify sequentially every significant demographic feature in the data and give it a parametric structural form. We demonstrate using U.K. mortality data that the general procedure produces a relatively parsimonious model that nevertheless has a good fit to the data.

Suggested Citation

  • Andrew Hunt & David Blake, 2014. "A General Procedure for Constructing Mortality Models," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 116-138.
    • Handle: RePEc:taf:uaajxx:v:18:y:2014:i:1:p:116-138
    DOI: 10.1080/10920277.2013.852963
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    Cited by:

    1. Salvatore Scognamiglio & Mario Marino, 2023. "Backtesting stochastic mortality models by prediction interval-based metrics," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3825-3847, August.
    2. 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.
    3. 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.
    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. Schinzinger, Edo & Denuit, Michel M. & Christiansen, Marcus C., 2016. "A multivariate evolutionary credibility model for mortality improvement rates," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 70-81.
    6. Carfora, M.F. & Cutillo, L. & Orlando, A., 2017. "A quantitative comparison of stochastic mortality models on Italian population data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 198-214.
    7. Börger, Matthias & Schupp, Johannes, 2018. "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 369-380.
    8. Graziani, Rebecca & NIGRI, ANDREA, 2023. "An Age–Period–Cohort Model in a Dirichlet Framework: A Coherent Causes of Death Estimation," SocArXiv 856yw, Center for Open Science.
    9. Chong It Tan & Jackie Li & Johnny Siu-Hang Li & Uditha Balasooriya, 2016. "Stochastic modelling of the hybrid survival curve," Journal of Population Research, Springer, vol. 33(4), pages 307-331, December.
    10. Karim Barigou & Stéphane Loisel & Yahia Salhi, 2020. "Parsimonious Predictive Mortality Modeling by Regularization and Cross-Validation with and without Covid-Type Effect," Risks, MDPI, vol. 9(1), pages 1-18, December.
    11. Ufuk Beyaztas & Hanlin Shang, 2022. "Machine-Learning-Based Functional Time Series Forecasting: Application to Age-Specific Mortality Rates," Forecasting, MDPI, vol. 4(1), pages 1-15, March.
    12. Gary Venter, 2018. "Regularized Age-Period-Cohort Modeling of Opioid Mortality Rates," Applied Economics and Finance, Redfame publishing, vol. 5(4), pages 12-23, July.
    13. 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.
    14. David Atance & Ana Debón & Eliseo Navarro, 2020. "A Comparison of Forecasting Mortality Models Using Resampling Methods," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    15. 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.
    16. I. A. Lakman & R. A. Askarov & V. B. Prudnikov & Z. F. Askarova & V. M. Timiryanova, 2021. "Predicting Mortality by Causes in the Republic of Bashkortostan Using the Lee–Carter Model," Studies on Russian Economic Development, Springer, vol. 32(5), pages 536-548, September.
    17. Kevin Dowd & David Blake, 2022. "Projecting Mortality Rates to Extreme Old Age with the CBDX Model," Forecasting, MDPI, vol. 4(1), pages 1-11, February.
    18. 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.
    19. Marcin Bartkowiak, 2018. "Mortality modelling. Model specification and mortality forecast accuracy," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 51, pages 13-36.
    20. 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.
    21. Redondo Lourés, Cristian & Cairns, Andrew J.G., 2021. "Cause of death specific cohort effects in U.S. mortality," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 190-199.
    22. Ka Kin Lam & Bo Wang, 2021. "Robust Non-Parametric Mortality and Fertility Modelling and Forecasting: Gaussian Process Regression Approaches," Forecasting, MDPI, vol. 3(1), pages 1-21, March.
    23. Sergio Alvares Maffra & John Armstrong & Teemu Pennanen, 2020. "Stochastic modeling of assets and liabilities with mortality risk," Papers 2005.09974, arXiv.org.
    24. Doukhan, P. & Pommeret, D. & Rynkiewicz, J. & Salhi, Y., 2017. "A class of random field memory models for mortality forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 97-110.

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