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Bayesian forecasting of mortality rates by using latent Gaussian models
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Alexopoulos, Angelos, Dellaportas, Petros and Forster, Jonathan J. (2019) Bayesian forecasting of mortality rates by using latent Gaussian models. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182 (2). pp. 689-711. doi:10.1111/rssa.12422 ISSN 0964-1998.
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WRAP-bayesian-forecasting-mortality-rates-using-latent-gaussian-models-Forster-2018.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons: Attribution-Noncommercial 4.0. Download (879Kb) | Preview |
Official URL: http://dx.doi.org/10.1111/rssa.12422
Abstract
We provide forecasts for mortality rates by using two different approaches. First we employ dynamic non‐linear logistic models based on the Heligman–Pollard formula. Second, we assume that the dynamics of the mortality rates can be modelled through a Gaussian Markov random field. We use efficient Bayesian methods to estimate the parameters and the latent states of the models proposed. Both methodologies are tested with past data and are used to forecast mortality rates both for large (UK and Wales) and small (New Zealand) populations up to 21 years ahead. We demonstrate that predictions for individual survivor functions and other posterior summaries of demographic and actuarial interest are readily obtained. Our results are compared with other competing forecasting methods.
| Item Type: | Journal Article | |||||||||
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| Subjects: | C Auxiliary Sciences of History > CB History of civilization H Social Sciences > H Social Sciences (General) H Social Sciences > HB Economic Theory H Social Sciences > HG Finance Q Science > QA Mathematics |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | |||||||||
| Library of Congress Subject Headings (LCSH): | Actuarial science, Mortality -- Statistics , Gaussian Markov random fields, Forecasting, Vital statistics | |||||||||
| Journal or Publication Title: | Journal of the Royal Statistical Society: Series A (Statistics in Society) | |||||||||
| Publisher: | Wiley | |||||||||
| ISSN: | 0964-1998 | |||||||||
| Official Date: | 15 January 2019 | |||||||||
| Dates: |
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| Volume: | 182 | |||||||||
| Number: | 2 | |||||||||
| Page Range: | pp. 689-711 | |||||||||
| DOI: | 10.1111/rssa.12422 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 28 January 2020 | |||||||||
| Date of first compliant Open Access: | 28 January 2020 | |||||||||
| RIOXX Funder/Project Grant: |
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