A comparison of official population projections with Bayesian time series forecasts for England and Wales


Abel, Guy J., Bijak, Jakub and Raymer, James (2010) A comparison of official population projections with Bayesian time series forecasts for England and Wales. Population Trends, 141, (1), Autumn Issue, 95-114. (doi:10.1057/pt.2010.23). (PMID:20927031).

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Description/Abstract

We compare official population projections with Bayesian time series forecasts for England and Wales. The Bayesian approach allows the integration of uncertainty in the data, models and model parameters in a coherent and consistent manner. Bayesian methodology for time-series forecasting is introduced, including autoregressive (AR) and stochastic volatility (SV) models. These models are then fitted to a historical time series of data from 1841 to 2007 and used to predict future population totals to 2033. These results are compared to the most recent projections produced by the Office for National Statistics. Sensitivity analyses are then performed to test the effect of changes in the prior uncertainty for a single parameter. Finally, in-sample forecasts are compared with actual population and previous official projections. The article ends with some conclusions and recommendations for future work.

Item Type: Article
ISSNs: 0307-4463 (print)
2040-1590 (electronic)
Related URLs:
Subjects: H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
Faculty of Social and Human Sciences > Social Sciences > Social Statistics & Demography
ePrint ID: 182735
Date Deposited: 28 Apr 2011 10:19
Last Modified: 27 Mar 2014 19:38
Research Funder: ESRC
Projects:
Centre for Population Change: Understanding Population Change in the 21st Century
Funded by: ESRC (RES-625-28-0001)
Led by: Jane Cecelia Falkingham
1 January 2009 to 31 December 2013
Publisher: ESRC Centre for Population Change
URI: http://eprints.soton.ac.uk/id/eprint/182735

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