Abstract Title
Equal Convergence?: Convergence Patterns Among Immigrants by Occupation
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Additional Funding Sources
This research was supported by Idaho State University and by the student researcher, Gwyneth Donahue.
Abstract
This study examines the immigrant-native wage gap in the United States using 2019 Annual Social and Economic Supplement data from the Current Population Survey. Ordinary least squares regression analyses were used to estimate and compare the wages of immigrants and native-born workers while controlling for factors such as education, sociodemographic characteristics, and time since arrival in the United States. The results demonstrate that the wage gap between immigrant and native-born workers diminishes with more time spent in the United States, likely due to increased work experience and language proficiency, but is not completely eliminated. Separate regressions are conducted for different occupational groups of varying skill levels. Occupations are shown to be a large contributor to the differential, as wages differ significantly more in unskilled occupations such as manual labor or transportation. The possibility of labor market discrimination is explored as a reason for the wage gap, with the Blinder-Oaxaca decomposition showing that only 68% of the wage gap can be explained by the included explanatory variables.
Equal Convergence?: Convergence Patterns Among Immigrants by Occupation
This study examines the immigrant-native wage gap in the United States using 2019 Annual Social and Economic Supplement data from the Current Population Survey. Ordinary least squares regression analyses were used to estimate and compare the wages of immigrants and native-born workers while controlling for factors such as education, sociodemographic characteristics, and time since arrival in the United States. The results demonstrate that the wage gap between immigrant and native-born workers diminishes with more time spent in the United States, likely due to increased work experience and language proficiency, but is not completely eliminated. Separate regressions are conducted for different occupational groups of varying skill levels. Occupations are shown to be a large contributor to the differential, as wages differ significantly more in unskilled occupations such as manual labor or transportation. The possibility of labor market discrimination is explored as a reason for the wage gap, with the Blinder-Oaxaca decomposition showing that only 68% of the wage gap can be explained by the included explanatory variables.