Imputation Match Bias in Immigrant Wage Convergence

Joni Hersch and Jennifer Bennett Shinall ()
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Jennifer Bennett Shinall: Vanderbilt University

No 11306, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Although immigrants to the United States earn less at entry than their native-born counterparts, an extensive literature finds that immigrants have faster earnings growth that results in rapid convergence to native-born earnings. However, recent evidence based on Census data indicates a slowdown in the rate of earnings assimilation. We find that the pace of immigrant wage convergence based on recent data may be understated in the literature due to the method used by the Census to impute missing information on earnings, which does not use immigration status as a match characteristic. Because both the share of immigrants in the workforce and earnings imputation rates have risen over time, imputation match bias for recent immigrants is more consequential than in earlier periods and may lead to an underestimate of the rate of immigrant wage convergence.

Keywords: imputation match bias; immigrant assimilation (search for similar items in EconPapers)
JEL-codes: J15 J31 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2018-01
New Economics Papers: this item is included in nep-mig
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Citations: View citations in EconPapers (1)

Published - published in: Demography, 2018, 55 (4), 1475-1485

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Journal Article: Imputation Match Bias in Immigrant Wage Convergence (2018)
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