Longevity forecasting by socio-economic groups using compositional data analysis

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review


  • Søren Kjærgaard, University of Southern Denmark, Aarhus University
  • ,
  • Yunus Emre Ergemen
  • Marie-Pier Bergeron-Boucher, University of Southern Denmark
  • ,
  • Jim Oeppen, University of Southern Denmark
  • ,
  • Malene Kallestrup-Lamb

Several Organisation for Economic Co-operation and Development countries have recently implemented an automatic link between the statutory retirement age and life expectancy for the total population to ensure sustainability in their pension systems due to increasing life expectancy. As significant mortality differentials are observed across socio-economic groups, future changes in these differentials will determine whether some socio-economic groups drive increases in the retirement age, leaving other groups with fewer pensionable years. We forecast life expectancy by socio-economic groups and compare the forecast performance of competing models by using Danish mortality data and find that the most accurate model assumes a common mortality trend. Life expectancy forecasts are used to analyse the consequences of a pension system where the statutory retirement age is increased when total life expectancy is increasing.

Original languageEnglish
JournalJournal of the Royal Statistical Society, Series A (Statistics in Society)
Pages (from-to)1167-1187
Number of pages21
Publication statusPublished - 2020

    Research areas

  • Compositional data, Forecasting, Longevity, Pension, Socio-economic groups

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