Smooth projection of mortality improvement rates: a Bayesian two-dimensional spline approach

Xiaobai Zhu, Kenneth Q. Zhou

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a spline mortality model for generating smooth projections of mortality improvement rates. In particular, we follow the two-dimensional cubic B-spline approach developed by Currie et al. (Stat Model 4(4):279–298, 2004), and adopt the Bayesian estimation and LASSO penalty to overcome the limitations of spline models in forecasting mortality rates. The resulting Bayesian spline model not only provides measures of stochastic and parameter uncertainties, but also allows external opinions on future mortality to be consistently incorporated. The mortality improvement rates projected by the proposed model are smoothly transitioned from the historical values with short-term trends shown in recent observations to the long-term terminal rates suggested by external opinions. Our technical work is complemented by numerical illustrations that use real mortality data and external rates to showcase the features of the proposed model.

Original languageEnglish (US)
JournalEuropean Actuarial Journal
DOIs
StateAccepted/In press - 2022
Externally publishedYes

Keywords

  • Bayesian estimation
  • External information
  • LASSO penalty
  • Spline mortality modeling
  • Stochastic mortality forecasting
  • The MIM-2021 model

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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