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Accuracy of Local Authority Population Forecasts Produced by a New Minimal Data Model: A Case Study of England

Author

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  • Philip Rees

    (University of Leeds)

  • Tom Wilson

    (The University of Melbourne)

Abstract

The preparation of forecasts for small and local area populations involves many challenges. Standard cohort-component models are problematic because of small numbers, which make estimation of rates unreliable. Because of this, the Synthetic Migration Population Projection (SYMPOPP) model was designed to forecast local populations without need for detailed area-specific information. This model had been used successfully for small area forecasts in Australia. The objective of the paper is to assess its performance when applied to local areas in England. The model uses a bi-regional structure based on a movement population account. Sub-models of total population change are employed to control future change. Fertility, mortality and migration rates are borrowed from national statistics, constrained to small area indicators. The model uses an Excel workbook with VBA routines and is relatively easy and quick to use. Model inputs were calibrated for 2006–2011 and used to forecast for 2011–2021. Results were tested against the census-based 2021 mid-year populations. A new error statistic, Age Structure Error, was used to evaluate Basic and Refined model versions against official projections. The two versions of SYMPOPP posted lower errors. The simple models had fewer areas with errors of 10% or more (12.3–12.6%) compared with the official projections (14.5% of areas). Investigation revealed that these errors occurred in local authorities with high military, student, prison, or ethnic minority populations, influenced by factors not captured in a projection model for the general population.

Suggested Citation

  • Philip Rees & Tom Wilson, 2023. "Accuracy of Local Authority Population Forecasts Produced by a New Minimal Data Model: A Case Study of England," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(6), pages 1-30, December.
    • Handle: RePEc:kap:poprpr:v:42:y:2023:i:6:d:10.1007_s11113-023-09839-2
    DOI: 10.1007/s11113-023-09839-2
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    References listed on IDEAS

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    1. Tom Wilson, 2022. "Preparing local area population forecasts using a bi-regional cohort-component model without the need for local migration data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 46(32), pages 919-956.
    2. Tom Wilson & Fiona Shalley, 2019. "Subnational population forecasts: Do users want to know about uncertainty?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(13), pages 367-392.
    3. Jeff Tayman & David A. Swanson & Jack Baker, 2021. "Using Synthetic Adjustments and Controlling to Improve County Population Forecasts from the Hamilton–Perry Method," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(6), pages 1355-1383, December.
    4. Mathew E. Hauer & Carl P. Schmertmann, 2020. "Population Pyramids Yield Accurate Estimates of Total Fertility Rates," Demography, Springer;Population Association of America (PAA), vol. 57(1), pages 221-241, February.
    5. Tom Wilson, 2016. "Evaluation of Alternative Cohort-Component Models for Local Area Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 35(2), pages 241-261, April.
    6. Aude Bernard & Martin Bell, 2015. "Smoothing internal migration age profiles for comparative research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(33), pages 915-948.
    7. Joseph Harrison & Katherine Lisa Keenan & Frank Sullivan & Hill Kulu, 2023. "Union formation and fertility amongst immigrants from Pakistan and their descendants in the United Kingdom: A multichannel sequence analysis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(10), pages 271-320.
    8. Jeff Tayman, 2011. "Assessing Uncertainty in Small Area Forecasts: State of the Practice and Implementation Strategy," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 30(5), pages 781-800, October.
    9. Tom Wilson & Huw Brokensha & Francisco Rowe & Ludi Simpson, 2018. "Insights from the Evaluation of Past Local Area Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(1), pages 137-155, February.
    10. Stanley Smith & Jeff Tayman, 2003. "An evaluation of population projections by age," Demography, Springer;Population Association of America (PAA), vol. 40(4), pages 741-757, November.
    11. Mario Reinhold & Stephan Thomsen, 2015. "Subnational Population Projections by Age: An Evaluation of Combined Forecast Techniques," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 34(4), pages 593-613, August.
    12. repec:cai:popine:popu_p1973_28n1_0129 is not listed on IDEAS
    13. Stanley Smith, 1986. "Accounting for migration in cohort-component projections of state and local populations," Demography, Springer;Population Association of America (PAA), vol. 23(1), pages 127-135, February.
    14. Erengul Dodd & Jonathan J. Forster & Jakub Bijak & Peter W. F. Smith, 2021. "Stochastic modelling and projection of mortality improvements using a hybrid parametric/semi-parametric age–period–cohort model," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2021(2), pages 134-155, February.
    15. Stephan Kolassa & Wolfgang Schütz, 2007. "Advantages of the MAD/Mean Ratio over the MAPE," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 6, pages 40-43, Spring.
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