The Problem of False Positives in Automated Census Linking: Evidence from Nineteenth-Century New York's Irish Immigrants

Tyler Anbinder, Dylan Connor, Cormac Ó Gráda and Simone Wegge

No 202114, Working Papers from School of Economics, University College Dublin

Abstract: Automated census linkage algorithms have become popular for generating longitudinal data on social mobility, especially for immigrants and their children. But what if these algorithms are particularly bad at tracking immigrants? Using nineteenth-century Irish immigrants as a test case, we examine the most popular of these algorithms—that created by Abramitzky, Boustan, Eriksson (ABE), and their collaborators. Our findings raise serious questions about the quality of automated census links. False positives range from about one-third to one-half of all links depending on the ABE variant used. These bad links lead to sizeable estimation errors when measuring Irish immigrant social mobility.

Keywords: Immigration; Census record matching; Social mobility (search for similar items in EconPapers)
JEL-codes: J61 N21 R23 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2021-06
New Economics Papers: this item is included in nep-his, nep-mig and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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http://hdl.handle.net/10197/12278 First version, 2021 (application/pdf)

Related works:
Working Paper: The Problem of False Positives in Automated Census Linking: Evidence from Nineteenth-Century New York's Irish Immigrants (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:ucn:wpaper:202114

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