Essays in higher education policy [electronic resource]
Keywords: Economics

In this dissertation, I use administrative databases from the state of Texas to address substantive issues in higher education policy. Chapter two, joint with Jesse Cunha, evaluates a novel program designed to increase college enrollment among students who are academically prepared for higher education but unlikely to enter on their own. The program sets up "GO Centers" that provide information about college, influence students' beliefs about the benefits of college, expedite the application process, and facilitate peer support for college. We estimate the program's impact on college application, acceptance, enrollment, and persistence rates using a differences-in-differences methodology where a propensity score matching procedure is used to identify schools that were in fact untreated but which closely matched the program's criteria for treatment. The findings indicate that the program had a large positive impact on all outcome measures, especially amongst Hispanic and low-income students. Chapter Three, also joint with Jesse Cunha, explores issues surrounding the measurement of the value-added by individual colleges and offers preliminary value-added estimates for all public colleges in Texas. Our problem differs from that of the primary and secondary educational system as college students specialize their instruction by choosing both school and major. Because wages are a measure of productivity, we argue for the use of labor market returns as a measure of value-added. Using administrative data from Texas, we estimate the labor market return to attending each of the 33 individual public colleges in the state. We present unconditioned estimates and find that labor differences are large. We then control for a rich array of observables that might be correlated with college choice, including demographics, SAT scores, parental income and education, local labor market conditions, high school GPA and course-taking patterns, and college major, and the vectors of college application decisions and subsequent acceptances. Upon conditioning, labor market returns across colleges tend to converge, yet significant differences remain. In Chapter 4, I examine the validity of distance to college as an instrument for educational attainment in earnings models. Numerous studies have used distance to college to instrument for educational attainment in models of the economic return to higher education. The assumption is that, conditional upon the included covariates, distance impacts educational attainment, but not earnings. One key problem with this assumption is the possibility that college location may be nonrandom. In this study, we use a large administrative database from the state of Texas to investigate the appropriateness of the use of distance to instrument for educational attainment and college choice in models of the labor market return to higher education. I show that colleges tend to locate in urban areas with robust local labor markets, and that IV models are highly sensitive to the exclusion of such information. I also show that distance instruments are highly sensitive to functional form in the first stage model.