Bayesian population forecasting: extending the Lee-Carter Method
Bayesian population forecasting: extending the Lee-Carter Method
In this article, we develop a fully integrated and dynamic Bayesian approach to forecast populations by age and sex. The approach embeds the Lee-Carter type models for forecasting the age patterns, with associated measures of uncertainty, fertility, mortality, immigration, and emigration within a cohort projection model. The methodology may be adapted to handle different data types and sources of information. To illustrate, we analyze time series data for the United Kingdom and forecast the components of population change to the year 2024. We also compare the results obtained from different forecast models for age-specific fertility, mortality, and migration. In doing so, we demonstrate the flexibility and advantages of adopting the Bayesian approach for population forecasting and highlight areas where this work could be extended.
Bayesian, Lee-Carter model, population forecasting, uncertainty, United Kingdom
1035-1059
Wisniowski, Arkadiusz
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Smith, Peter W.F.
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Bijak, Jakub
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Raymer, James
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Forster, Jonathan J.
e3c534ad-fa69-42f5-b67b-11617bc84879
June 2015
Wisniowski, Arkadiusz
ec9da054-45f0-4393-ad91-87e8f9750ae9
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Forster, Jonathan J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Wisniowski, Arkadiusz, Smith, Peter W.F., Bijak, Jakub, Raymer, James and Forster, Jonathan J.
(2015)
Bayesian population forecasting: extending the Lee-Carter Method.
Demography, 52 (3), .
(doi:10.1007/s13524-015-0389-y).
Abstract
In this article, we develop a fully integrated and dynamic Bayesian approach to forecast populations by age and sex. The approach embeds the Lee-Carter type models for forecasting the age patterns, with associated measures of uncertainty, fertility, mortality, immigration, and emigration within a cohort projection model. The methodology may be adapted to handle different data types and sources of information. To illustrate, we analyze time series data for the United Kingdom and forecast the components of population change to the year 2024. We also compare the results obtained from different forecast models for age-specific fertility, mortality, and migration. In doing so, we demonstrate the flexibility and advantages of adopting the Bayesian approach for population forecasting and highlight areas where this work could be extended.
Text
Wisniowski_et_al_2015_Demography.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 1 January 2015
e-pub ahead of print date: 12 May 2015
Published date: June 2015
Additional Information:
Open access: Full text is freely available from the publisher's website
Keywords:
Bayesian, Lee-Carter model, population forecasting, uncertainty, United Kingdom
Organisations:
Social Statistics & Demography, Statistics, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 379875
URI: http://eprints.soton.ac.uk/id/eprint/379875
ISSN: 0070-3370
PURE UUID: d1a5fb78-4da4-4ebe-971d-7115384c9455
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Date deposited: 24 Aug 2015 11:30
Last modified: 15 Mar 2024 03:34
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Contributors
Author:
Arkadiusz Wisniowski
Author:
James Raymer
Author:
Jonathan J. Forster
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