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Stochastic modelling and projection of mortality improvements using a hybrid parametric/semi-parametric age–period–cohort model
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Dodd, Erengul, Forster, Jonathan J., Bijak, Jakub and Smith, Peter W. F. (2021) Stochastic modelling and projection of mortality improvements using a hybrid parametric/semi-parametric age–period–cohort model. Scandinavian Actuarial Journal, 2021 (2). pp. 134-155. doi:10.1080/03461238.2020.1815238 ISSN 0346-1238.
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Official URL: http://dx.doi.org/10.1080/03461238.2020.1815238
Abstract
We propose a comprehensive and coherent approach for mortality projection using a maximum-likelihood method which benefits from full use of the substantial data available on mortality rates, their improvement rates, and the associated variability. Under this approach, we fit a negative binomial distribution to overcome one of the several limitations of existing approaches such as insufficiently robust mortality projections as a result of employing a model (e.g. Poisson) which provides a poor fit to the data. We also impose smoothness in parameter series which vary over age, cohort, and time in an integrated way. Generalised Additive Models (GAMs), being a flexible class of semi-parametric statistical models, allow us to differentially smooth components, such as cohorts, more heavily in areas of sparse data for the component concerned. While GAMs can provide a reasonable fit for the ages where there is adequate data, estimation and extrapolation of mortality rates using a GAM at higher ages is problematic due to high variation in crude rates. At these ages, parametric models can give a more robust fit, enabling a borrowing of strength across age groups. Our projection methodology assumes a smooth transition between a GAM at lower ages and a fully parametric model at higher ages.
Item Type: | Journal Article | ||||||||||
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Subjects: | H Social Sciences > HB Economic Theory | ||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||
Library of Congress Subject Headings (LCSH): | Mortality -- Statistical methods, Life expectancy, Bayesian statistical decision theory, Projection, Linear models (Statistics) | ||||||||||
Journal or Publication Title: | Scandinavian Actuarial Journal | ||||||||||
Publisher: | Routledge | ||||||||||
ISSN: | 0346-1238 | ||||||||||
Official Date: | March 2021 | ||||||||||
Dates: |
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Volume: | 2021 | ||||||||||
Number: | 2 | ||||||||||
Page Range: | pp. 134-155 | ||||||||||
DOI: | 10.1080/03461238.2020.1815238 | ||||||||||
Status: | Peer Reviewed | ||||||||||
Publication Status: | Published | ||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||
Date of first compliant deposit: | 31 August 2022 | ||||||||||
Date of first compliant Open Access: | 31 August 2022 | ||||||||||
RIOXX Funder/Project Grant: |
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