Imputation Match Bias in Immigrant Wage Convergence

17 Pages Posted: 6 Feb 2018

See all articles by Joni Hersch

Joni Hersch

Vanderbilt University - Law School; IZA Institute of Labor Economics; Vanderbilt University - Owen Graduate School of Management; Vanderbilt University - College of Arts and Science - Department of Economics

Jennifer Bennett Shinall

Vanderbilt University - Law School

Multiple version iconThere are 2 versions of this paper

Date Written: January 2018

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: immigrant assimilation, imputation match bias

JEL Classification: J15, J31

Suggested Citation

Hersch, Joni and Shinall, Jennifer Bennett, Imputation Match Bias in Immigrant Wage Convergence (January 2018). IZA Discussion Paper No. 11306, Available at SSRN: https://ssrn.com/abstract=3117310

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Jennifer Bennett Shinall

Vanderbilt University - Law School ( email )

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Nashville, TN 37203-1181
United States

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