A Test of the Validity of Imputed Legal Immigration Status

Bibliographic Data

ID10970144
AuthorsMarcelo Castillo (0000-0002-8462-1896, Economic Research Service, corresponding author), Alexandra Hill (0000-0002-3996-1541, University of California System), Thomas Hertz (Unaffiliated)
Year2024
Volume61
Issue2
Pages283-306
Publication date2024-04-01
Open AccessYes
TypeARTICLE
VenueDemography (JOURNAL)
Journal identifiersISSN: 0070-3370 • E-ISSN: 1533-7790
PublisherDuke University Press (PUBLISHER • US)
DOI10.1215/00703370-11189687
PMID38386492
OpenAlexW4392031992
LanguageEN
Citations received2
References cited35

We evaluate the performance of a widely used technique for imputing the legal immigration status of U.S. immigrants in survey data—the logical imputation method. We validate this technique by implementing it in a nationally representative survey of U.S. farmworkers that includes a well-regarded measure of legal status. When using this measure as a benchmark, the imputation algorithm correctly identifies the legal status of 78% of farmworkers. Of all the variables included in the algorithm, we find that Medicaid participation poses the greatest challenge for accuracy. Using the American Community Survey, we show that increased Medicaid enrollments stemming from the implementation of the Affordable Care Act in 2014 led to sizable changes in the share of immigrants imputed as legal over time and across space. We explore the implications of these changes for two previous studies and conclude that including Medicaid criteria in the imputation algorithm can significantly impact research findings. We also provide tools to gauge the sensitivity of results

Actuarial science · American Community Survey · Business · Census · Environmental health · Health care · Immigration · Imputation (statistics · Legal status · Machine learning · Medicaid · Missing data · Political science · Population · Statistics · Survey data collection · Computer Science · Employment and Welfare Studies · Law · Mathematics · Medicine · Migration and Labor Dynamics · Migration, Health and Trauma · Psychology

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