Linked samples and measurement error in historical US census data

Sam Il Myoung Hwang and Munir Squires

Explorations in Economic History, 2024, vol. 93, issue C

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.

Keywords: Intergenerational mobility; Measurement error; Data linkage (search for similar items in EconPapers)
JEL-codes: C55 J62 N00 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:exehis:v:93:y:2024:i:c:s0014498324000093

DOI: 10.1016/j.eeh.2024.101579

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