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Estimating the civilian noninstitutional population for small areas: a modified cohort component approach using public use data

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  • Andrew C. Forrester

    (U.S. Bureau of Labor Statistics)

Abstract

This article develops a demographic method to estimate the civilian noninstitutional population for counties and county equivalents in the U.S. While these data provide the key sampling frame for national labor market surveys and denominators for labor market prevalence rates, the data are thus far unavailable for small areas. I develop a modified cohort component method to produce novel, monthly estimates of the civilian noninstitutional population for all U.S. counties using publicly available data on population and vital statistics with minimal modifications. The resulting population data may be used by researchers and policymakers to study within-year population dynamics as they relate to economic and demographic factors. I further extend the method to produce short-term population projections that include the most current vital statistics. The method compares favorably to existing annual, midyear estimates by the U.S. Census Bureau, but is prone to error in areas with fewer vital events.

Suggested Citation

  • Andrew C. Forrester, 2024. "Estimating the civilian noninstitutional population for small areas: a modified cohort component approach using public use data," Journal of Population Research, Springer, vol. 41(1), pages 1-31, March.
    • Handle: RePEc:spr:joprea:v:41:y:2024:i:1:d:10.1007_s12546-023-09322-x
    DOI: 10.1007/s12546-023-09322-x
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    References listed on IDEAS

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    1. Craig A. Feinstein, 2002. "Seasonality of Deaths in the U.S. by Age and Cause," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(17), pages 471-488.
    2. David Lam & Jeffrey Miron, 1996. "The effects of temperature on human fertility," Demography, Springer;Population Association of America (PAA), vol. 33(3), pages 291-305, August.
    3. 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.
    4. Tom Wilson & Irina Grossman & Monica Alexander & Phil Rees & Jeromey Temple, 2022. "Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 865-898, June.
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    More about this item

    Keywords

    Population estimation and projections; Model specification; Small areas;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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