Black Population Size and the Structure of United States Labor Market Inequality
Philip N. Cohen
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Philip N. Cohen: University of Maryland, College Park
No 4sn6k, Thesis Commons from Center for Open Science
This dissertation investigates the relationship between relative Black population size and the structure of labor market inequality by race-ethnicity, gender and class. There are five principal new developments here. First, Black-White inequality for women -- as well as gender inequality -- is integrated into the research. Second, by examining three major labor market outcomes -- employment status, occupational attainment, and earnings -- the project offers a more systematic view of the relationships under study. This has important implications for better understanding possible causal mechanisms of racial-ethnic composition. Third, existing threat and crowding hypotheses are tested with new models using measures of residential and occupational segregation. Fourth, tests of class interactions are offered, casting new light on continuing debates about the relative costs and benefits of Black-White inequality across class and gender lines. Finally, estimation of contextual effects in all models is improved with hierarchical modeling techniques. Larger relative Black population size means more "race" in the local economy, and more "racial" inequality. This project asks the question: is more "race" good or bad for White and Black men and women at the individual level; whom does Black-White inequality help or hurt, and in what ways? I conclude that when the Black population is larger, Black-White inequality is more salient, and more important relative to class and gender inequality. A consistent set of models shows this pattern across labor market outcomes, and across gender and class groups -- as well as across variation in individual-level characteristics besides racial-ethnicity. Thus Black-White inequality again appears not only pervasive but also structural to the system of social stratification in the United States.
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