Bayesian population forecasts for England and Wales

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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Identifiers

ORCID for Jakub Bijak: orcid.org/0000-0002-2563-5040

ORCID for Jonathan J. Forster: orcid.org/0000-0002-7867-3411

ORCID for Peter W.F. Smith: orcid.org/0000-0003-4423-5410

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