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A Hermite spline approach for modelling population mortality

Published online by Cambridge University Press:  17 October 2022

Sixian Tang Open the ORCID record for Sixian Tang [Opens in a new window] ,
Jackie Li Open the ORCID record for Jackie Li [Opens in a new window]  and
Leonie Tickle Open the ORCID record for Leonie Tickle [Opens in a new window]
Sixian Tang*
Affiliation:
Department of Econometrics and Business Statistics, Monash University, Melbourne, VIC, Australia School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA, Australia
Jackie Li
Affiliation:
Department of Econometrics and Business Statistics, Monash University, Melbourne, VIC, Australia
Leonie Tickle
Affiliation:
Department of Actuarial Studies and Business Analytics, Macquarie University, Sydney, NSW, Australia
*
*Corresponding author. E-mail: sixian.tang@monash.edu
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Abstract

One complication in mortality modelling is capturing the impact of risk factors that contribute to mortality differentials between different populations. Evidence has suggested that mortality differentials tend to diminish over age. Classical methods such as the Gompertz law attempt to capture mortality patterns over age using intercept and slope parameters, possibly causing an unjustified mortality crossover at advanced ages when applied independently to different populations. In recent research, Richards (Scandinavian Actuarial Journal 2020(2), 110–127) proposed a Hermite spline (HS) model that describes the age pattern of mortality differentials using one parameter and circumvents an unreasonable crossover by default. The original HS model was applied to pension data at individual level in the age dimension only. This paper extends the method to model population mortality in both age and period dimensions. Our results indicate that in addition to possessing desirable fitting properties, the HS approach can produce accurate mortality forecasts, compared with the Gompertz and P-splines models.

Keywords

Mortality forecastingHermite splinesMortality modelsLongevity risk
Type
Original Research Paper
Information
Annals of Actuarial Science , Volume 17 , Issue 2 , July 2023 , pp. 243 - 284
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Institute and Faculty of Actuaries

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