Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model

Silvia Rizzi , Søren Kjærgaard , Marie-Pier Bergeron-Boucher , Carlo Giovanni Camarda (1) , Rune Lindahl-Jacobsen , James W. Vaupel

1 INED - Institut national d'études démographiques

Mortality forecasting has crucial implications for insurance and pension policies. A large amount of literature has proposed models to forecast mortality using cross-sectional (period) data instead of longitudinal (cohort) data. As a consequence, decisions are generally based on period life tables and summary measures such as period life expectancy, which reflect hypothetical mortality rather than the mortality actually experienced by a cohort. This study introduces a novel method to forecast cohort mortality and the cohort life expectancy of non-extinct cohorts. The intent is to complete the mortality profile of cohorts born up to 1960. The proposed method is based on the penalized composite link model for ungrouping data. The performance of the method is investigated using cohort mortality data retrieved from the Human Mortality Database for England & Wales, Sweden, and Switzerland for male and female populations.

Mots clés: Mortality forecasting; Cohort life tables; Cohort mortality forecasts; Demographic forecasting; Non-extinct cohorts; Smoothing; models

Domaines: Sciences de l'Homme et Société

Silvia Rizzi, Søren Kjærgaard, Marie-Pier Bergeron-Boucher, Carlo Giovanni Camarda, Rune Lindahl-Jacobsen, et al.. Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model. International Journal of Forecasting, 2020, Online First, ⟨10.1016/j.ijforecast.2020.03.003⟩. ⟨hal-02557687⟩