This dissertation explores the effectiveness and consequences of three distinct education policies. The first chapter analyzes the effects of high school exit exams on graduation, employment and wage outcomes. We construct a state-graduation year cohort dataset using the Current Population Survey data, US Census data and information on the timing and difficulty of exit exams in different states. Using this dataset we analyze within-state variation in outcomes overtime. Overall, we find relatively modest effects of high school exit exams. We do not find consistent effects on graduation rates for exit exams that assess academic skills taught below the high school level; however, we find that more challenging standards-based exams reduce graduation rates. We also find that about one-half of the reduction in graduation rates associated with exit exams is offset by an increase in GED rates. Our analysis of labor market outcomes suggests that exit exams increase employment rates, but we find no effect of exit exams on the distribution of wages. Chapter two analyzes the institutional consequences of the California Class-Size Reduction (CSR) program. This program provides incentive funding if schools limit the class-size in grades K-3 to twenty or fewer students. We find that some schools and school districts limit their enrollment levels in order to maximize the CSR subsidy payment. In particular, the distribution of grade and district enrollments exhibits a prominent pattern of peaks that occur at multiples of twenty, where CSR payment is the largest. In order to achieve exact enrollment levels, schools must be reassigning students above the desired thresholds to nearby schools or nearby school districts. We also find that schools that limit their enrollments are well-performing schools with a low percentage of students who receive free or reduced price meals. The last chapter analyzes the academic consequences of the Texas Top 10 Percent Law. In 1998, state universities in Texas began using high school class rank as the sole factor in university admissions. This policy was implemented to increase enrollment of minority and economically disadvantaged students, but it generated criticism that such beneficiaries of rank-based admissions lack the academic preparation necessary to perform well in college. I test this claim by analyzing academic performance of rank-eligible students who attended UT Austin before and after the law. To account for grade inflation I use a difference-in-differences framework with students not eligible for rank-based admissions as controls. The difference-in-differences estimates may be overstated, however, because academic quality of the control group may have increased after the law. I use propensity score matching methods to correct for this. Finally, I correct for the confounding effects of GPA ceiling on the difference-in-differences estimates. Both the baseline and the adjusted estimates suggest that mean college GPA of rank-admitted students declined after the law.

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This study examines the messages and accuracy of the messages sent to students from the Arizona Instrument to Measure Standards (AIMS) math test regarding academic preparedness for postsecondary education. Previous studies investigating messages sent to students, derived from information such as educational standards, grades, course taking policies, test material, and college admissions requirements, focused on content alignment of secondary and postsecondary content standards. However, a dearth of research exists on messages from high school performance, as measured by exit exams and college performance measured by grades, major selection, or graduation. This study addresses the need to understand and interpret messages students receive based on academic performance. Specifically, this study aims to answer three questions. First, what is the relationship between AIMS math scores and college math performance defined by the University of Arizona math requirement and college graduation? Second, to what degree do AIMS math scores predict college math performance? Third, what is the average AIMS math score and performance level for students who choose certain majors? To answer the research questions posed in this study, various statistical analyses were employed. To answer the first question, a one-way ANOVA and logistic regression analyses were used. A linear regression analysis served to analyze the second and third questions. Results indicate that the messages sent to students regarding college readiness are, in fact, well aligned and clear and consistent. Also, there is evidence that the messages vary by gender and ethnicity.

Goals 2000 and No Child Left behind have developed a new timeline for language acquisition, have promoted the practice of teaching to the test rather than the understanding of content, and High School Exit Exams have led to the widening of the achievement gap between ELL students and their Non-ELL counterparts. In additions, the policies’ narrow definition of success leads to federal sanctions that penalize schools with ELL student populations further contributing to the widening of the gap.

The purpose of this study was to examine the variables that are associated with the percentage of students who pass Tennessee's Gateway exams in high school. Associations were examined between the Gateway exams and variables such as: socioeconomic status, ethnicity, dropout rate, graduation rate, attendance, average daily membership, per-pupil expenditure, teachers' salary, and elementary-school reading scores. Pearson correlations between school characteristics and pass rates of three Gateway exams were calculated. Schools were divided into quartiles based upon socioeconomic status and ethnicity in order to examine pass rates of the Gateway exams among different quartiles. Independent samples t tests were performed to determine if differences were statistically significant. Variables that exhibited strong association with pass rates of Gateway exams were used as predictor variables and pass rates of Gateway exams were used as dependent variables in multivariable linear regressions. The findings indicated that the graduation rate and percentage of Caucasian students were most positively associated with Gateway pass rates. Dropout rates and percentage of students who qualified for free/reduced-priced meals were most negatively associated with Gateway pass rates. It was discovered that the Algebra I Gateway exam was by far the most difficult for students to pass. Almost half of the students in high schools serving poor, minority students failed the Algebra I Gateway exam in 2004.