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Bayesian population forecasting: extending the Lee-Carter Method

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
0070-3370
1035-1059
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
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), 1035-1059. (doi:10.1007/s13524-015-0389-y).

Record type: Article

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.

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Wisniowski_et_al_2015_Demography.pdf - Accepted Manuscript
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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
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410
ORCID for Jakub Bijak: ORCID iD orcid.org/0000-0002-2563-5040
ORCID for Jonathan J. Forster: ORCID iD orcid.org/0000-0002-7867-3411

Catalogue record

Date deposited: 24 Aug 2015 11:30
Last modified: 15 Mar 2024 03:34

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Contributors

Author: Arkadiusz Wisniowski
Author: Jakub Bijak ORCID iD
Author: James Raymer
Author: Jonathan J. Forster ORCID iD

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