Mortality Projection Using Bayesian Model Averaging

Andrés Gustavo Benchimol (), Juan Miguel Marín Diazaraque (), Irene Albarrán Lozano () and Pablo Jesús Alonso-González ()
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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
Authors registered in the RePEc Author Service: Pablo J. Alonso González

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2018, pp 111-115 from Springer

Abstract: 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.

Keywords: Bayesian model averaging; Cairns-Blake-Dowd model; Lee-Carter model; Longevity; Model uncertainty; Mortality projection; Renshaw-Haberman model (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-89824-7_20

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DOI: 10.1007/978-3-319-89824-7_20

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