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The limits of predicting individual-level longevity

Author

Listed:
  • Luca Badolato

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Ari Gabriel Decter-Frain

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Nicolas Irons

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Maria Laura Miranda

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Erin Walk
  • Elnura Zhalieva
  • Monica J. Alexander

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Ugofilippo Basellini

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Emilio Zagheni

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

Individual-level mortality prediction is a fundamental challenge with implications for life planning, social policies and public spending. We model and predict individual-level lifespan using 12 traditional and state-of-the-art models and over 150 predictors derived from the U.S. Health and Retirement Study. Machine learning and statistical models report comparable accuracy and relatively high discriminative performance, but fail to account for most lifespan heterogeneity at the individual level. We observe consistent inequalities in mortality predictability and risk discrimination, with lower accuracy for men, non-Hispanic Blacks, and low-educated individuals. Additionally, people in these groups show lower accuracy in their subjective predictions of their own lifespan. Finally, top features across groups are similar, with variables related to habits, health history, and finances being relevant predictors. We conclude by highlighting the limits of predicting mortality from representative surveys and the inequalities across social groups, providing baselines and guidance for future research and public policies.

Suggested Citation

  • Luca Badolato & Ari Gabriel Decter-Frain & Nicolas Irons & Maria Laura Miranda & Erin Walk & Elnura Zhalieva & Monica J. Alexander & Ugofilippo Basellini & Emilio Zagheni, 2023. "The limits of predicting individual-level longevity," MPIDR Working Papers WP-2023-008, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2023-008
    DOI: 10.4054/MPIDR-WP-2023-008
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    References listed on IDEAS

    as
    1. Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
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    More about this item

    Keywords

    USA; forecasts; inequality; longevity;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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