Abstract
We measure the empirical distribution of the accuracy of projected population in sub-national areas of England, developing the concept of ‘shelf life’: the furthest horizon for which the subsequent best estimate of population is within 10% of the forecast, for at least 80% of areas projected. Since local government reorganisation in 1974, the official statistics agency has projected the population of each local government area in England: for 108 areas in nine forecasts up to the 1993-based, and for over 300 areas in 10 forecasts from the 1996-based to the 2014-based forecasts. By comparing the published forecast (we use this term rather than projection) with the post-census population estimates, the empirical distribution of errors has been described. It is particularly dependent on the forecast horizon and the type of local authority. For 10-year forecasts the median absolute percentage error has been 7% for London Boroughs and 3% for Shire Districts. Users of forecasts tend to have in mind a horizon and a required accuracy that is of relevance to their application. A shelf life of 10 years is not sufficient if the user required that accuracy of a forecast 15 years ahead. The relevant effective shelf life deducts the user’s horizon. We explore the empirical performance of official sub-national forecasts in this light. A five-year forecast for London Boroughs requiring 10% accuracy is already beyond its effective shelf life by the time it is published. Collaboration between forecasters and users of forecasts can develop information on uncertainty that is useful to planning.
Highlights
IntroductionAre population forecasts acceptably accurate for those who make decisions based on them?
Are population forecasts acceptably accurate for those who make decisions based on them? A simple answer would take the continued reliance of decision-makers on population forecasts as an indication of their acceptance
We have examined the results from both approaches and they differ in small ways rather than in the pattern or the general conclusions, but we believe that our use of absolute percentage deviation (APD) for our results on error distribution and shelf life give more direct answers to the user’s question ‘How far is the truth likely to be from this forecast?’
Summary
Are population forecasts acceptably accurate for those who make decisions based on them? A simple answer would take the continued reliance of decision-makers on population forecasts as an indication of their acceptance. It uses the results to provide confidence intervals around 2016-based forecasts, and uses the concept of ‘shelflife’ (Wilson et al 2018) to provide an answer to the question of the forecasts’ quality. These official forecasts are cohort component forecasts with age and sex disaggregation; in this paper we look only at the accuracy of the forecast of total population
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