Bayesian time series models for forecasting population growth in England and Wales

James Raymer, University of Southampton
Jakub Bijak, University of Southampton
Peter W.F. Smith, University of Southampton
Guy J. Abel, University of Southampton
Jonathan J. Forster, University of Southampton

The Bayesian approach has a number of attractive properties for forecasting uncertainty that have yet to be fully explored in the study of future population change. In this presentation, we first apply some simple Bayesian time series models to obtain future population estimates for England and Wales, along with measures of uncertainty. To account for heterogeneity found in the historical data, we add parameters to represent the stochastic volatility in the error terms. Uncertainty in model choice is incorporated through Bayesian model averaging techniques. Second, we present a more complex multivariate time series model that includes the demographic components of change. The forecasts of population growth from both models are then compared, followed by some conclusions and proposals for future research.

Presented in Session 40: Modelling demographic change in the context of uncertainty