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Cognition, a component of human capital, is fundamental for decision-making, and understanding the causes of human capital depreciation in old age is especially important in aging societies. Using various proxy measures of cognitive performance from a longitudinal survey in South Africa, we study how education affects cognition in late adulthood. We show that an extra year of schooling improves memory performance and general cognition. We find evidence of heterogeneous effects by gender: the effects are stronger among women. We explore potential mechanisms, and we show that a more supportive social environment, improved health habits, and reduced stress levels likely play a critical role in mediating the beneficial effects of educational attainment on cognition among the elderly.
In this paper I study the impact of court-mandated school desegregation by race on student suspensions and special education classification. Simple descriptive statistics using student enrollment and outcome data collected from the largest school districts across the country in the 1970s and 1980s show that Black-White school integration was increasing for districts under court order, but not for a set of comparison districts. Similarly, Black student suspension rates were increasing at faster rates in integrating districts relative to comparison districts, and their classification rates as having an intellectual disability were decreasing at slower rates. Differences-in-differences and event study models confirm these patterns I observe in the raw data: after integration, school districts experienced statistically and practically significant reductions in racial isolation across schools and growth in racial disparities in discipline and special education classification. The impacts of integration are immediate, sustained, and robust for student suspensions in particular. My results thus provide causal evidence confirming prior descriptive and theoretical work suggesting that the racial composition of schools may influence measures of categorical inequality by race.
Using detailed classroom-level data for North Carolina, we build on previous research to examine racial gaps in access to high-quality teachers. We calculate the exposure of White, Black and Hispanic students to teachers with various characteristics in 4th grade, 7th grade math and English, and 10th grade math and English. We find that across the state White students enjoy sizable advantages over both Black and Hispanic students in the form of higher exposure to teachers with strong credentials and lower exposure to teachers with weak credentials. Remarkably, we also find this pattern of White advantage in most individual counties, with the largest White advantage occurring in the largest counties by enrollment. A decomposition of the White advantages shows that the bulk of them can be attributed to differences across counties and differences between schools within counties. Only in 10th grade are differences across classrooms within schools important in explaining the White advantage.
The COVID-19 pandemic led to an abrupt shift from in-person to virtual instruction in Spring 2020. Using two complementary difference-in-differences frameworks, one that incorporates student fixed effects and another that leverages within-course variation on whether students started their Spring 2020 courses in-person or online, we estimate the impact of this shift on the academic performance of Virginia’s community college students. With both approaches, we find modest negative impacts (four to eight percent) on course completion. Our results suggest that faculty experience teaching a given course online does not mitigate the negative effects of students abruptly switching to online instruction.
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.
Levels of governance (the nation, states, and districts), student subgroups (racial and ethnic minoritized and economically disadvantaged students), and types of resources (expenditures, class sizes, and teacher quality) intersect to represent a complex and comprehensive picture of K-12 educational resource inequality. Drawing on multiple sources of the most recently available data, we describe inequality in multiple dimensions. At the national level, racial and ethnic minoritized and economically disadvantaged students receive less K-12 expenditures per pupil than White and economically advantaged students (between $400 to $1,200 less per pupil). At the state and district levels, racial and ethnic minoritized and economically disadvantaged students receive more K-12 expenditures per pupil than white and economically advantaged students (between $200 to $400 more). The notable exception is Hispanic students, who receive no additional funding per pupil than white students, on average, at the state level. Among districts, minoritized and economically disadvantaged students have smaller class sizes than their subgroup counterparts, but these students also have greater exposure to inexperienced teachers. About 20 percent of additional teacher hires favoring traditionally disadvantaged student subgroups is for novice teachers. We see no evidence that district-level spending in favor of traditionally disadvantaged subgroups is explained by district size, average district spending, teacher turnover, or the size of the special education population.
We use novel data on disciplinary referrals, including those that do not lead to suspensions, to better understand the origins of racial disparities in exclusionary discipline. We find significant differences between Black and white students in both referral rates and the rate at which referrals convert to suspensions. An infraction fixed-effects research design that compares the disciplinary outcomes of white and non-white students who were involved in the same multi-student incident identifies systematic racial biases in sentencing decisions. On both the intensive and extensive margins, minoritized students receive harsher sentences than their white co-conspirators. This result is driven by high school infractions and applies to all infraction types. Reducing racial disparities in exclusionary discipline will require addressing underlying gaps in disciplinary referrals and the systematic biases that appear in the adjudication process.
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.