Essays on Worker Skills and the Black-White Male Unemployment Gap in the United States

This dissertation is composed of two chapters examining how differences in experience and skill development, over the life-cycle of workers, shape the unemployment gap between black and white male workers in the United States. Understanding these mechanisms is crucial since the black-white unemployment gap remains a persistent feature of the US labor market across the past several decades. In the first chapter, I study the impact of differences in life-cycle skill development on the black-white unemployment gap for high-school-educated male workers. Using a shift-share framework, I document the inability of differences in labor composition across observable characteristics such as education, age, industry, and occupation to explain the majority of the black-white male unemployment gap. I then develop a search and matching framework with worker heterogeneity across skill levels. Calibrating the model separately for black and white high-school-educated male workers, I identify differences across i) skill development patterns and ii) the returns to skill development over the life cycle. Using the calibrated model, I find that differences in life cycle skill development patterns account for about 64 percent of the black-to-white unemployment ratio. Closing the racial gap in the returns to skill development decreases the unemployment ratio by 25 percent. Finally, the interaction between the two channels explains about 81 percent of the unemployment ratio. In the second chapter, I ask how differences in experience and life-cycle skill development impact the black-white male unemployment gap for college-educated workers. To address this question, I use the search and matching framework, developed in the first chapter, with heterogeneous workers across skill levels. I parameterize the model separately for black and white college-educated male workers, targeting key features of life-cycle wage growth and unemployment. The baseline calibration indicates the existence of racial differences across life-cycle skill development as well as returns to such skill development. Using the calibrated model, I find that differences in life-cycle skill development account for about 102 percent of the black-to-white unemployment ratio. Differences in the returns to life-cycle skill development explain about 17.18 percent of the unemployment ratio, while the interaction between the two channels explains about 111 percent of the unemployment ratio.