Using U.S. Census data fitted into a series of cross sectional quantitative models, this dissertation estimates how ethnoracialization molds immigrants’ socioeconomic outcomes, after controlling for their demographic and human capital endowments and the spatial context in which they live. Although extensive research exists on the relationship between human capital, income and social status and the unequal socioeconomic outcomes of immigrant groups, little attention has been given to how the ethnoracial heterogeneity within and between immigrant groups affects unequal outcomes. To contribute to fill this void, this dissertation presents three analyses that build on one another by exploring how ethnoracialization helps shape socioeconomic outcomes through time and space while paying particular attention to the interaction between country of origin, race, English proficiency, legal status, and the educational attainment of immigrants. The studies find evidence that strongly suggest the presence of structural ethnoracialization at the national, regional and metropolitan scales that mediates the economic integration of immigrants, especially those with high levels of education, into the U.S. economy. Specifically, results point to a patterned division of outcomes where immigrants from some Asian countries such as India and China are positively ethnoracialized, and consistently place at the top of all measured outcomes (income, socioeconomic status, occupational status, and skill-job matching probabilities), while Latin Americans, especially Mexicans and Central American, who tend to be negatively ethnoracialized, place at the bottom.