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

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Title: The Problem of False Positives in Automated Census Linking: Evidence from Nineteenth-Century New York's Irish Immigrants
Authors: Anbinder, TylerConnor, DylanÓ Gráda, CormacWegge, Simone
Permanent link: http://hdl.handle.net/10197/12278
Date: Jun-2021
Online since: 2021-06-22T10:18:01Z
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.
Funding Details: George Washington University
CUNY Research Foundation
National Endowment for the Humanities
Type of material: Working Paper
Publisher: University College Dublin. School of Economics
Start page: 1
End page: 55
Series/Report no.: UCD Centre for Economic Research Working Paper Series; WP2021/14
Copyright (published version): 2021 the Authors
Keywords: ImmigrationCensus record matchingSocial mobility
JEL Codes: N21; J61; R23
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Economics Working Papers & Policy Papers

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