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Linked samples and measurement error in historical US census data

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  • Hwang, Sam Il Myoung
  • Squires, Munir

Abstract

The quality of historical US census data is critical to the performance of linking algorithms. We use genealogical profiles to correct measurement error in census names and ages. Our findings suggest that one in every two records has an error in name or age, and human capital is correlated with lower error rates. While errors in age decline across subsequent census rounds from 1850 to 1930, errors in names do not exhibit such trends. Fixing all transcription errors, hence leaving only those errors made at the time of enumeration, would reduce error rates in names by 41 percent. Correcting all names and ages using genealogical profiles leads to 20%–36% more links and fewer false positives. Reassuringly, we find that reducing such errors has a negligible effect on estimates of intergenerational mobility.

Suggested Citation

  • Hwang, Sam Il Myoung & Squires, Munir, 2024. "Linked samples and measurement error in historical US census data," Explorations in Economic History, Elsevier, vol. 93(C).
    • Handle: RePEc:eee:exehis:v:93:y:2024:i:c:s0014498324000093
    DOI: 10.1016/j.eeh.2024.101579
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    1. de Julian, Mikel, 2025. "Economic Outcomes of the Great Migration in the U.S. South," SocArXiv 5gw9p_v1, Center for Open Science.

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    More about this item

    Keywords

    Intergenerational mobility; Measurement error; Data linkage;
    All these keywords.

    JEL classification:

    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • N00 - Economic History - - General - - - General

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