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A Simplified Version of the Hamilton–Perry Method for Forecasting Population by Age Group and Gender

Author

Listed:
  • Jeff Tayman

    (Tayman Demographics)

  • David A. Swanson

    (Portland State University
    University of Washington
    University of California Riverside)

Abstract

Following the concept of utility, this paper examines a way to reduce further the time and cost associated with an already cost-effective approach to population forecasting, the Hamilton–Perry method (H–P method), which not only has been found to produce reasonably accurate forecasts but has a wide range of applications, including stable population theory and historical demography. The usual application of the H–P method, H–P-Usual, is based on gender-specific CCRs and CWRs, using the female population in the childbearing years to compute the CWRs. H–P-Usual has potential drawbacks. If population forecasts by age are only needed for the total population, additional time and resources are required to assemble and evaluate the gender-specific CCRs and CWRs. More pressing, especially for subcounty areas, is the issue of small population sizes in the age and gender-specific population cells. One potential solution to these issues is reducing the number of input cells required by the H–P model. We propose a simpler H–P method, H–P-Light, that uses non-gender-specific CCRs and CWRs. We analyzed 10-year forecast errors for US counties and census tracts and found no degradation of performance using H–P-Light in both counties and census tracts. We conclude that H–P-Light is a viable alternative to H–P-Usual for producing age-specific population forecasts for the total population and, if needed, by gender.

Suggested Citation

  • Jeff Tayman & David A. Swanson, 2025. "A Simplified Version of the Hamilton–Perry Method for Forecasting Population by Age Group and Gender," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 44(3), pages 1-33, June.
  • Handle: RePEc:kap:poprpr:v:44:y:2025:i:3:d:10.1007_s11113-025-09951-5
    DOI: 10.1007/s11113-025-09951-5
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    References listed on IDEAS

    as
    1. 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.
    2. Stefan Rayer & Stanley Smith & Jeff Tayman, 2009. "Empirical Prediction Intervals for County Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 28(6), pages 773-793, December.
    3. Neal Marquez & Xiaoqi Bao & Eileen Kazura & Jessica Lapham & Priya Sarma & Crystal Yu & Christine Leibbrand & Sara Curran, 2024. "An Evaluation of Projection Methods for Detailed Small Area Projections: An Application and Validation to King County, Washington," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(2), pages 1-29, April.
    4. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    5. Armstrong, J. Scott, 2006. "Findings from evidence-based forecasting: Methods for reducing forecast error," International Journal of Forecasting, Elsevier, vol. 22(3), pages 583-598.
    6. Jeff Tayman & David Swanson, 1996. "On the utility of population forecasts," Demography, Springer;Population Association of America (PAA), vol. 33(4), pages 523-528, November.
    7. Jeff Tayman & David A. Swanson, 2017. "Using modified cohort change and child-woman ratios in the Hamilton–Perry forecasting method," Journal of Population Research, Springer, vol. 34(3), pages 209-231, September.
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