A dynamic parameterization modeling for the age-period-cohort mortality

P. Hatzopoulos and S. Haberman

Insurance: Mathematics and Economics, 2011, vol. 49, issue 2, 155-174

Abstract: An extended version of Hatzopoulos and Haberman (2009) dynamic parametric model is proposed for analyzing mortality structures, incorporating the cohort effect. A one-factor parameterized exponential polynomial in age effects within the generalized linear models (GLM) framework is used. Sparse principal component analysis (SPCA) is then applied to time-dependent GLM parameter estimates and provides (marginal) estimates for a two-factor principal component (PC) approach structure. Modeling the two-factor residuals in the same way, in age-cohort effects, provides estimates for the (conditional) three-factor age-period-cohort model. The age-time and cohort related components are extrapolated using dynamic linear regression (DLR) models. An application is presented for England & Wales males (1841-2006).

Keywords: Cohort; Mortality; forecasting; Generalized; linear; models; Sparse; principal; component; analysis; Factor; analysis; Dynamic; linear; regression; Bootstrap; confidence; intervals (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:49:y:2011:i:2:p:155-174

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