TRACING THE EFFECTS OF GUARANTEED ADMISSION THROUGH THE COLLEGE PROCESS: EVIDENCE FROM A POLICY DISCONTINUITY IN THE TEXAS 10% PLAN

I. INTRODUCTION The Texas 10% law states that a student who graduates among the top 10% of her high school class is guaranteed admission to public universities in Texas. Consequently, students just inside the top 10% and students just outside the top 10% are treated differently in the college admissions process. This leads to different incentives for the two groups of students and different treatment of these students by the admissions committees at the schools. Ultimately, the differential treatment by the law and the resulting choices can lead to differences in educational outcomes. In this article, we examine the effects of the 10% rule on a sequence of connected decisions: students' application behavior, admission decisions by the university, students' enrollment choices conditional on admission; as well as the resulting college achievement. Intuitively, our identification strategy amounts to comparing students just above and just below the top 10% high school class rank cut off. We examine if we are able to detect a discrete jump in probabilities of application, admission, or enrollment at the top 10% cut off. Then, we look for discontinuities in student performance conditional on these decisions. We make two contributions. First, we estimate the behavioral consequences of an admissions guarantee. Second, under the assumption that the total number of slots at a university is-fixed tin the short term) we can contribute to the evaluation of the 10% rule by comparing the marginal student enrolled due to the rule to the marginal student not enrolled due to the rule. We use complete administrative data from the two flagship universities: the University of Texas at Austin (UT) and Texas A&M University at College Station (A&M). We do not find evidence that the admissions guarantee increases applications to a specific flagship university. We do find some limited evidence that the law affects the characteristics of applicants. For example, the admissions guarantee seems to encourage students with lower SAT scores to apply to A&M. At UT it leads to slightly more applicants from high schools that traditionally do not send many students to the university, suggesting a broadening of the applicant pool related to the law. Our results also suggest spillover effects on applications to institutions not covered by the law. The admissions guarantee to public universities leads to a drop in applications to private universities (Rice and Southern Methodist University [SMU]), suggesting that guaranteed admission at UT or A&M makes applications to the private schools less valuable. We are able to show that the 10% law is binding and does alter admissions decisions conditional on application--mainly at UT. While students in the top 10% are always admitted, students just outside the top 10% have an 80% acceptance rate at UT and a 95% rate at A&M. On the margin, the admissions guarantee changes the characteristics of the admitted students conditional on application. At UT it leads to more admissions of students from ethnic minorities and from high schools that traditionally provide few students to the university. At both universities it leads to the admission of more female students. In contrast, we find no differences in the SAT test score performance for students admitted with or without admissions guarantee. Conditional on admission, students in the top high school decile are more likely to enroll at A&M than students just outside the top decile, which suggests that the admissions guarantee leads to applications of students for whom A&M is the preferred school among their eventual options. At UT the result is reversed. It is possible that students in the top 10% of their high school use UT as their backup plan--a "high quality safety school" with guaranteed admission. If they are admitted at a preferred school, they do not enroll at UT. Next, we look at the students who eventually enroll at A&M or UT. …