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Longevity forecasting by socio-economic groups using compositional data analysis

Author

Listed:
  • Søren Kjærgaard

    (University of Southern Denmark)

  • Yunus Emre Ergemen

    (University of Aarhus and CREATES)

  • Marie-Pier Bergeron Boucher

    (University of Southern Denmark)

  • Jim Oeppen

    (University of Southern Denmark)

  • Malene Kallestrup-Lamb

    (University of Aarhus and CREATES)

Abstract

Several OECD countries have recently implemented an automatic link between the statutory retirement age and life expectancy for the total population to insure sustainability in their pension systems when life expectancy is increasing. Significant mortality differentials are observed across socio-economic groups and future changes in these differentials will determine whether some socio-economic groups drive increases in the retirement age leaving other groups with fewer years in receipt of pensions. We forecast life expectancy by socio-economic groups and compare the forecast performance of competing models 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

Suggested Citation

  • Søren Kjærgaard & Yunus Emre Ergemen & Marie-Pier Bergeron Boucher & Jim Oeppen & Malene Kallestrup-Lamb, 2019. "Longevity forecasting by socio-economic groups using compositional data analysis," CREATES Research Papers 2019-08, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2019-08
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Compositional data; forecasting; longevity; pension; socioeconomic groups;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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