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Author: Jiang, Shengjun
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1. Jiang, Shengjun
Essays on College Major, College Curriculum, and Subsequent Labor Market Outcomes
Ph.D. Dissertation, Department of Economics, The Ohio State University, 2019
Cohort(s): NLSY97
Publisher: ProQuest Dissertations & Theses (PQDT)
Keyword(s): College Graduates; College Major/Field of Study/Courses; Gender Differences; Grade Point Average (GPA)/Grades; Job Characteristics; Job Satisfaction; Labor Market Outcomes; Occupations; Wage Effects; Wage Gap; Wage Penalty/Career Penalty

Permission to reprint the abstract has not been received from the publisher.

In the first chapter, I estimate wage effects of double majors and double degrees among a sample of college graduates in their early career, using the 1997 National Longitudinal Survey of Youth (NLSY97). I rely on selection on observables and control for individuals’ test scores, family background, and school characteristics when estimating the wage effects. I further consider whether wage effects of a double major/degree can be explained by two mechanisms: the "skill-enhancing" effect (increase in the depth of knowledge accumulated in college) and the "job-matching" effect (increase in the chance of working in an occupation that is more closely related to one's college major). I examine whether estimated wage effects associated with a double major/degree (after controlling for confounding factors) decrease as a result of controlling for the depth of knowledge accumulated in college and the relatedness between college major and occupation. I find that having a double major does not make a significant difference in one's early-career post-college wages. A double degree is estimated to be associated with a 0.088 increase in log wages after controlling for confounding factors. About a third of this effect can be explained by a combination of both the "skill-enhancing" and "job-matching" effects. In the second chapter, I use the NLSY97 to study whether being mismatched in the first job (meaning the individual's occupation is not among the common occupations to which his/her college major typically leads) has a long-lasting effect on wages. I also investigate wage growth and job change patterns for different types of mismatched workers. I distinguish between demand-side mismatch due to job dissatisfaction and supply-side mismatch due to reasons other than reported job dissatisfaction. I find that both types of mismatched workers have significantly lower wages compared to matched workers, but that demand-side mismatched workers face a larger wage penalty than do supply-side mismatched workers. However, the wage penalty associated with demand-side mismatch reduces about 1.6 times as fast as does the penalty of supply-side mismatch as labor market experience increases. The result is that the estimated log-wage effect of mismatch virtually disappears in six years for both demand-side and supply-side mismatched workers, even though the former face a large wage penalty at the outset. Further, I show that demand-side mismatched workers tend to have more between-job mobility and between-job wage growth than matched workers, whereas supply-side mismatched workers tend to have more within-job mobility and within-job wage growth than matched workers. Overall, job mobility and subsequent wage growth contribute to the closure of the wage gap between matched and mismatched workers. My findings support predictions stemming from the job match literature that wage effects of first-job mismatches are not long-lasting. In the last chapter, I use NLSY97 data to determine the extent to which detailed measures of college-related factors, based on course credits and grades earned in different fields of study, explain the gender wage gap among college graduates in their early career. I start with a standard set of controls and then add my detailed measures of college-related factors to identify the increase in the explained gender wage gap. A decomposition of the gender wage gap reveals that the inclusion of detailed measures of college-related factors along with the standard set of controls increases the explained part of the estimated gender wage gap from 65.6% to 69.1%-77.8%. Among all the pre-market factors, detailed measures of college-related factors have the most explanatory power to the estimated gender wage gap (28.5%-39.1%). My findings imply that gender differences in credits and grades earned in different fields of study capture additional gender differences in skills that cannot be fully represented by gender differences in other factors such as college major and occupation. Compared to gender differences in college major and general academic achievement, gender differences in credits and grades earned in different fields of study are better pre-market measures for differences in skills between college-educated men and women.
Bibliography Citation
Jiang, Shengjun. Essays on College Major, College Curriculum, and Subsequent Labor Market Outcomes. Ph.D. Dissertation, Department of Economics, The Ohio State University, 2019.