A Hermite spline approach for modelling population mortality

Sixian Tang, Jackie Li, Leonie Tickle

Research output: Contribution to journalArticleResearchpeer-review


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 Journal2020(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.
Original languageEnglish
Pages (from-to)243-284
Number of pages42
JournalAnnals of Actuarial Science
Issue number2
Publication statusPublished - Jul 2023


  • Mortality forecasting
  • Hermite splines
  • Mortality models
  • Longevity risk

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