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We investigate how the presence of a college affects local educational attainment using historical natural experiments in which "runner-up" locations were strongly considered to become college sites but ultimately not chosen for as-good-as-random reasons. While runner-up counties have since had opportunity to establish their own colleges, winners are still more likely to have a college today. Using this variation, we find that winning counties today have college degree attainment rates 58% higher than runner-up counties and have larger shares of employment in high human capital sectors. These effects are not driven primarily by college employees, migration, or local development.
This study investigates whether a principal’s likelihood of hiring a teacher of color is sensitive to the racial composition of students in the school. We used an administrative dataset from Texas including 59,157 principal observations and 662,997 teacher observations spanning 2000 to 2017 in order to consider whether or not the disappearing diversity from a majority white school is a factor in principals’ decisions to hire teachers of color. We examined the hiring patterns of principals within schools where 50% of the students were white and compared the probability that a nonwhite teacher would be hired as the homogeneity of the student body increased (that is, as increasing proportions of the student body were white). We found that white principals were less likely to hire teachers of color as the proportion of white students approached 100%. This study provides initial evidence that teacher hires are not only sensitive to the principal’s race but also to the racial composition of the student body. Specifically, as the diversity of the student body disappears, so too does the principal’s likelihood of hiring a teacher of color.
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two important dimensions: (1) different approaches to sample and variable construction and how these affect model accuracy; and (2) how the selection of predictive modeling approaches, ranging from methods many institutional researchers would be familiar with to more complex machine learning methods, impacts model performance and the stability of predicted scores. The relative ranking of students’ predicted probability of completing college varies substantially across modeling approaches. While we observe substantial gains in performance from models trained on a sample structured to represent the typical enrollment spells of students and with a robust set of predictors, we observe similar performance between the simplest and most complex models.
Is public housing bad for children? Critics charge that public housing projects concentrate poverty and create neighborhoods with limited opportunities, including low-quality schools. However, whether the net effect is positive or negative is theoretically ambiguous and likely to depend on the characteristics of the neighborhood and schools compared to origin neighborhoods. In this paper, we draw on detailed individual-level longitudinal data on students moving into New York City public housing and examine their academic outcomes over time. Exploiting plausibly random variation in the precise timing of entry into public housing, we estimate credibly causal effects of public housing using both difference-in-differences and event study designs. We find credibly causal evidence of positive effects of moving into public housing on student test scores, with larger effects over time. Stalled academic performance in the first year of entry may reflect, in part, disruptive effects of residential and school moves. Neighborhood matters: effects are larger for students moving out of low-income neighborhoods or into higher-income neighborhoods, and these students move to schools with higher average test scores and lower shares of economically disadvantaged peers. We also find some evidence of improved attendance outcomes and reduction in incidence of childhood obesity for boys following public housing residency. Our study results refute the popular belief that public housing is bad for kids and probe the circumstances under which public housing may work to improve academic outcomes for low-income students.
Using administrative data from Georgia, we provide the first study of the full set of college entrance exam-taking strategies, including who takes the ACT and the SAT (or both), when they take the exams, and how many times they take each exam. We have several main findings. First, one-third of exam takers take both the ACT and SAT. Second, we see pronounced disparities in several measures of exam-taking strategy by free- and reduced-price lunch status, even after including a rich set of controls, but not by underrepresented minority status. Third, we find evidence that taking more total exams leads to higher admissions-relevant test scores and a higher likelihood of enrolling in colleges with relatively high graduation rates and earnings. However, these relationships with test scores and college enrollment are smaller for those who take both the ACT and SAT, as opposed to retaking the same exam multiple times.
Despite interest in the role of school discipline in the creation of racial inequality, previous research has been unable to identify how students who receive suspensions in school differ from unsuspended classmates on key young adult outcomes. We utilize novel data to document the links between high school discipline and important young adult outcomes related to criminal justice contact, social safety net program participation, post-secondary education, and the labor market. We show that the link between school discipline and young adult outcomes tends to be stronger for Black students than for White students, and that inequality in exposure to school discipline accounts for approximately 30 percent of the Black-White disparities in young adult criminal justice outcomes and SNAP receipt.
Over the past four decades, income inequality grew significantly between workers with bachelor’s degrees and those with high school diplomas (often called “unskilled”). Rather than being unskilled, we argue that these workers are STARs because they are skilled through alternative routes—namely their work experience. Using the skill requirements of a worker’s current job as a proxy of their actual skill, we find that though both groups of workers make transitions to occupations requiring similar skills to their previous occupations, workers with bachelor’s degrees have dramatically better access to higher wage occupations where the skill requirements exceed the workers’ observed skill. This measured opportunity gap offers a fresh explanation of income inequality by degree status and reestablishes the important role of on-the-job-training in human capital formation.
Third grade is oftentimes the first year standardized literacy assessments are mandated. In turn many policies aimed at improving literacy have focused on third-grade test scores as a key indicator. Yet literacy struggles begin well before third grade, as do racial and socioeconomic disparities in children’s literacy skills. Kindergarten readiness assessments provide a unique opportunity to better understand the emergence of literacy disparities. We use unique kindergarten literacy data from nearly every school district in Virginia to document the relationship between children’s early literacy skills and their later reading proficiency. Comparing children with similar literacy skills at kindergarten entry, we find significant racial and socioeconomic differences in the likelihood a child is proficient on their third-grade reading assessment.
Federal law defines eligibility for English learner (EL) classification differently for Indigenous students compared to non-Indigenous students. Indigenous students, unlike non-Indigenous students, are not required to have a non-English home or primary language. A critical question, therefore, is how EL classification impacts Indigenous students’ educational outcomes. This study explores this question for Alaska Native students, drawing on data from five Alaska school districts. Using a regression discontinuity design, we find evidence that among students who score near the EL classification threshold in kindergarten, EL classification has a large negative impact on Alaska Native students’ academic outcomes, especially in the 3rd and 4th grades. Negative impacts are not found for non-Alaska Native students in the same districts.
Under the Individuals with Disabilities Education Act, schools are required to provide a free and appropriate public education to students with disabilities and show that the students are making academic progress. This study compares within- and across-years academic growth from kindergarten to 4th grade for students who were ever in special education (ever-SPED) to students who were never in special education (never-SPED). We follow one cohort of about 4,200 students for five years and assess the students up to three times per year. Although ever-SPED students started kindergarten with lower math and reading test scores and grew less in both subjects than never-SPED students during the kindergarten school year, ever-SPED students grew more than never-SPED students during the 1st and 2nd grade school years in math and 1st, 3rd, and 4th grade school years in reading. However, ever-SPED students lost more learning during every summer than never-SPED students. This led the test score disparities between the two to grow from under 0.5 standard deviations in kindergarten to 1.0 standard deviation in 4th grade. These findings suggest that summer learning opportunities are crucial for improving educational outcomes for students with disabilities.