Project Activities
To examine the effect of graduating in the top 10 percent, the research team will use a statistical design that compares the outcomes of students just above and just below the 90th class rank percentile cutoff used to determine eligibility for automatic admissions to the University of Texas system. The second portion of the study will investigate whether geographic proximity influences attendance at elite flagship universities versus less-selective universities, as well investigating the academic impact for minorities of attending a selective versus a less-selective university.
Structured Abstract
Setting
This study examines high school graduates in Texas. The portion of the study examining percent plans focuses on graduates from three of the largest districts in Texas.
Sample
The analysis samples will be comprised of administrative records that contain information on students graduating from Texas public high schools.
Research design and methods
To examine the effect of graduating in the top 10 percent, the research team will use a regression discontinuity design that compares the academic and labor market outcomes of students just above and just below the 90th class rank percentile cutoff used to determine eligibility for automatic admissions to the University of Texas system. The second potion of the study will use the fact that students are more likely to attend a school close to where they live. Conditional on prior academic achievement, geographic proximity to one of the state's flagship campuses generates variation in the likelihood of attending a selective university that can be used to identify the causal impact of attending a selective versus a less-selective university.
Key measures
The research team will analyze measures of access to college such as whether a student applied to a Texas university (and to which one) and actual enrollment patterns. In addition, the data also allows the examination of measures of success in college including retention, credits accumulated, and receipt of academic degrees.
Data analytic strategy
The regression discontinuity analysis will employ parametric and non-parametric methods widely used in the literature to estimate the difference in student outcomes occurring at the automatic admissions eligibility cutoff. The analysis of the effect of attending a selective college will use "Instrumental Variables" (IV) methods. This approach exploits the fact that students living near a selective university are more likely to apply for admission there.
People and institutions involved
IES program contact(s)
Products and publications
Products: Products from this project include published reports on the impacts of graduating in the top 10 percent of one's high school class on student outcomes at selective and less-selective universities.
Journal article, monograph, or newsletter
Daugherty, L., Martorell, P., and McFarlin, I. (2014). Percent Plans, Automatic Admissions, and College Outcomes. IZA Journal of Labor Economics, 3(1), 10.
Supplemental information
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
