Mortality Projection Using Bayesian Model Averaging
Authors
Benchimol, Andrés Gustavo; Marín Diazaraque, Juan Miguel; Albarrán Lozano, Irene; Alonso González, Pablo JesúsIdentifiers
Permanent link (URI): http://hdl.handle.net/10017/60061DOI: 10.1007/978-3-319-89824-7
ISBN: 978-3-319-89824-7
Publisher
Springer International Publishing Switzerland
Date
2018-06-15Embargo end date
2100-01-25Affiliation
Universidad de Alcalá. Departamento de EconomíaBibliographic citation
Mathematical and Statistical Methods for Actuarial Sciences and Finance MAF 2018. Suiza: Springer International Publishing Switzerland, 2018, pp. 111-116
Document type
info:eu-repo/semantics/bookPart
Version
info:eu-repo/semantics/publishedVersion
Rights
© Springer International Publishing AG
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Access rights
info:eu-repo/semantics/embargoedAccess
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 consideringmodel 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.