Survival analysis of pension scheme mortality when data are missing

Francesco Ungolo, Marcus C. Christiansen, Torsten Kleinow, Angus S. Macdonald

Research output: Contribution to journalArticle

1 Citation (Scopus)
1 Downloads (Pure)

Abstract

Missing data is a problem that may be faced by actuaries when analysing mortality data. In this paper we deal with pension scheme data, where the future lifetime of each member is modelled by means of parametric survival models incorporating covariates, which may be missing for some individuals. Parameters are estimated by likelihood-based techniques. We analyse statistical issues, such as parameter identifiability, and propose an algorithm to handle the estimation task. Finally, we analyse the financial impact of including covariates maximally, compared with excluding parts of the mortality experience where data are missing; in particular we consider annuity factors and mis-estimation risk capital requirements.
Original languageEnglish
Pages (from-to)523-547
Number of pages25
JournalScandinavian Actuarial Journal
Volume2019
Issue number6
Early online date27 Feb 2019
DOIs
Publication statusPublished - 3 Jul 2019

Keywords

  • Mortality
  • longevity risk
  • missing data
  • mortality models with covariates
  • survival model

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Survival analysis of pension scheme mortality when data are missing'. Together they form a unique fingerprint.

Cite this