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Bayesian population forecasts for England and Wales

Bayesian population forecasts for England and Wales
Bayesian population forecasts for England and Wales
The Bayesian approach has a number of attractive properties for forecasting uncertainty which have yet to be fully explored in the study of future population change. In this paper, we apply some simple Bayesian time series models to obtain future population estimates with uncertainty for England and Wales. Uncertainty in model choice is incorporated through Bayesian model averaging techniques.

The resulting predictive distributions from Bayesian forecasting models have two main advantages over those obtained using more traditional stochastic models. First, uncertainties in the data,the model parameters and model choice are explicitly represented using probability distributions. As a result, more realistic probabilistic population forecasts are obtained. Second, Bayesian models formally allow the incorporation of expert opinion, including uncertainty, into the forecast. We conclude by discussing our results in relation to classical
time series methods and existing cohort component estimates.
WP37
Statistical Office of the European Union (EUROSTAT)
Abel, Guy J.
d35b5069-3c52-4d13-a678-1684ae1fce1e
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Forster, Jonathan J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Abel, Guy J.
d35b5069-3c52-4d13-a678-1684ae1fce1e
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Forster, Jonathan J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940

Abel, Guy J., Bijak, Jakub, Forster, Jonathan J., Raymer, James and Smith, Peter W.F. (2010) Bayesian population forecasts for England and Wales (Joint Eurostat/UNECE Work Session on Demographic Projections, WP37) Statistical Office of the European Union (EUROSTAT)

Record type: Monograph (Working Paper)

Abstract

The Bayesian approach has a number of attractive properties for forecasting uncertainty which have yet to be fully explored in the study of future population change. In this paper, we apply some simple Bayesian time series models to obtain future population estimates with uncertainty for England and Wales. Uncertainty in model choice is incorporated through Bayesian model averaging techniques.

The resulting predictive distributions from Bayesian forecasting models have two main advantages over those obtained using more traditional stochastic models. First, uncertainties in the data,the model parameters and model choice are explicitly represented using probability distributions. As a result, more realistic probabilistic population forecasts are obtained. Second, Bayesian models formally allow the incorporation of expert opinion, including uncertainty, into the forecast. We conclude by discussing our results in relation to classical
time series methods and existing cohort component estimates.

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Submitted date: 26 April 2010
Published date: 27 April 2010

Identifiers

Local EPrints ID: 151473
URI: https://eprints.soton.ac.uk/id/eprint/151473
PURE UUID: 9865abd9-deb3-4d09-b8ae-4cb44e22f09a
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
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410

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Date deposited: 11 May 2010 09:47
Last modified: 24 May 2019 00:38

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Contributors

Author: Guy J. Abel
Author: Jakub Bijak ORCID iD
Author: James Raymer

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