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Producing U.S. Population Statistics Using Multiple Administrative Sources

Author

Listed:
  • J. David Brown
  • Marta Murray-Close

Abstract

We identify several challenges encountered when constructing U.S. administrative record-based (AR-based) population estimates for 2020. Though the AR estimates are higher than the 2020 Census at the national level, they are over 15 percent lower in 5 percent of counties, suggesting that locational accuracy can be improved. Other challenges include how to achieve comprehensive coverage, maintain consistent coverage across time, filter out nonresidents and people not alive on the reference date, uncover missing links across person and address records, and predict demographic characteristics when multiple ones are reported or when they are missing. We discuss several ways of addressing these issues, e.g., building in redundancy with more sources, linking children to their parents’ addresses, and conducting additional record linkage for people without Social Security Numbers and for addresses not initially linked to the Census Bureau’s Master Address File. We discuss modeling to predict lower levels of geography for people lacking those geocodes, the probability that a person is a U.S. resident on the reference date, the probability that an address is the person’s residence on the reference date, and the probability a person is in each demographic characteristic category. Regression results illustrate how many of these challenges and solutions affect the AR county population estimates.

Suggested Citation

  • J. David Brown & Marta Murray-Close, 2023. "Producing U.S. Population Statistics Using Multiple Administrative Sources," Working Papers 23-58, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:23-58
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    File URL: https://www2.census.gov/library/working-papers/2023/adrm/ces/CES-WP-23-58.pdf
    File Function: First version, 2023
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    References listed on IDEAS

    as
    1. Carolyn A. Liebler & Sonya R. Porter & Leticia E. Fernandez & James M. Noon & Sharon R. Ennis, 2017. "America’s Churning Races: Race and Ethnicity Response Changes Between Census 2000 and the 2010 Census," Demography, Springer;Population Association of America (PAA), vol. 54(1), pages 259-284, February.
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    More about this item

    Keywords

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    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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