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 the wages of immigrants while controlling for human capital characteristics, sociodemographic factors, and time since arrival in the United States. The results demonstrate that the wage gap converges with more time spent in the United States, likely due to increased work experience and language proficiency, but does not completely diminish. Separate regressions are conducted for different occupational groups. 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.

本研究使用来自当前人口调查的 2019 年年度社会和经济补充数据，研究了美国移民与本地人的工资差距。使用普通最小二乘回归分析来估计移民的工资，同时控制人力资本特征、社会人口因素和抵达美国后的时间。结果表明，工资差距随着在美国停留时间的增加而趋同，这可能是由于工作经验和语言能力的增加，但并未完全缩小。对不同的职业群体进行了单独的回归。职业被证明是造成差异的一个重要因素，因为体力劳动或运输等非技术职业的工资差异更大。