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Mortality Projection Using Bayesian Model Averaging

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Andrés Gustavo Benchimol

    (The University of Hong Kong, Department of Statistics & Actuarial Science)

  • Juan Miguel Marín Diazaraque

    (Universidad Carlos III de Madrid, Department of Statistics)

  • Irene Albarrán Lozano

    (Universidad Carlos III de Madrid, Department of Statistics)

  • Pablo Jesús Alonso-González

    (Universidad de Alcalá, Economics Department)

Abstract

In this paper we propose Bayesian specifications of four of the most widespread models used for mortality projection: Lee-Carter, Renshaw-Haberman, Cairns-Blake-Dowd, and its extension including cohort effects. We introduce the Bayesian model averaging in mortality projection in order to obtain an assembled model considering model uncertainty. We work with Spanish mortality data from the Human Mortality Database, and results suggest that applying this technique yields projections with better properties than those obtained with the individual models considered separately.

Suggested Citation

  • Andrés Gustavo Benchimol & Juan Miguel Marín Diazaraque & Irene Albarrán Lozano & Pablo Jesús Alonso-González, 2018. "Mortality Projection Using Bayesian Model Averaging," Springer Books, in: Marco Corazza & María Durbán & Aurea Grané & Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 111-115, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-89824-7_20
    DOI: 10.1007/978-3-319-89824-7_20
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