A multivariate evolutionary credibility model for mortality improvement rates

Edo Schinzinger, Michel M. Denuit, Marcus Christiansen

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
145 Downloads (Pure)

Abstract

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
Volume69
Early online date27 Apr 2016
DOIs
Publication statusPublished - Jul 2016

Keywords

  • 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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