A multivariate evolutionary credibility model for mortality improvement rates

Edo Schinzinger*, Michel M. Denuit, Marcus Christiansen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
212 Downloads (Pure)


The present paper proposes an evolutionary credibility model that describes the joint dynamics of mortality through time in several populations. Instead of modeling the mortality rate levels, the time series of population-specific mortality rate changes, or mortality improvement rates are considered and expressed in terms of correlated time factors, up to an error term. Dynamic random effects ensure the necessary smoothing across time, as well as the learning effect. They also serve to stabilize successive mortality projection outputs, avoiding dramatic changes from one year to the next. Statistical inference is based on maximum likelihood, properly recognizing the random, hidden nature of underlying time factors. Empirical illustrations demonstrate the practical interest of the approach proposed in the present paper.

Original languageEnglish
Pages (from-to)70-81
Number of pages12
JournalInsurance: Mathematics and Economics
Early online date27 Apr 2016
Publication statusPublished - Jul 2016


  • ARMA process
  • Lee-Carter model
  • Mortality projection
  • Multi-population modeling
  • Predictive distribution

ASJC Scopus subject areas

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


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