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Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models

Content Provider	Springer Nature Link
Author	Tayman, Jeff Smith, Stanley K. Lin, Jeffrey
Copyright Year	2007
Abstract	Many researchers have used time series models to construct population forecasts and prediction intervals at the national level, but few have evaluated the accuracy of their forecasts or the out-of-sample validity of their prediction intervals. Fewer still have developed models for subnational areas. In this study, we develop and evaluate six ARIMA time series models for states in the United States. Using annual population estimates from 1900 to 2000 and a variety of launch years, base periods, and forecast horizons, we construct population forecasts for four states chosen to reflect a range of population size and growth rate characteristics. We compare these forecasts with population counts for the corresponding years and find precision, bias, and the width of prediction intervals to vary by state, launch year, model specification, base period, and forecast horizon. Furthermore, we find that prediction intervals based on some ARIMA models provide relatively accurate forecasts of the distribution of future population counts but prediction intervals based on other models do not. We conclude that there is some basis for optimism regarding the possibility that ARIMA models might be able to produce realistic prediction intervals to accompany population forecasts, but a great deal of work remains to be done before we can draw any firm conclusions.
Starting Page	347
Ending Page	369
Page Count	23
File Format	PDF
ISSN	01675923
Journal	Population Research and Policy Review
Volume Number	26
Issue Number	3
e-ISSN	15737829
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2007-06-23
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ARIMA Forecast accuracy Forecast uncertainty Population forecasts Prediction intervals Population Economics Economic Policy Economic Geography Demography
Content Type	Text
Resource Type	Article
Subject	Demography Management, Monitoring, Policy and Law

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Empirical Prediction Intervals for County Population Forecasts

Empirical Prediction Intervals for County Population Forecasts

Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models’. Population Research and Policy Review 26 (2007)

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Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models

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Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models’. Population Research and Policy Review 26 (2007)

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