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We examine the causal influence of educators elected to the school board on local education production. The key empirical challenge is that school board composition is endogenously determined through the electoral process. To overcome this, we develop a novel research design that leverages California's randomized assignment of the order that candidate names appear on election ballots. We find that an additional educator elected to the school board reduces charter schooling and increases teacher salaries in the school district relative to other board members. We interpret these findings as consistent with educator board members shifting bargaining in favor of teachers' unions.
A growing body of research and popular reporting shows racial differences in school modality choices during the COVID-19 crisis, with white students more likely to attend school in person. This in-person learning gap raises serious equity concerns. We use unique panel survey data to explore possible explanations. We find that a combination of factors may explain these differences. School districts’ offerings, political partisanship, and local COVID-19 outbreaks are all meaningfully associated with and plausibly explain the in-person learning racial gap. As schools start offering more in-person learning, significant efforts may be necessary to ensure that families and students attend those in-person learning opportunities.
This paper considers an unavoidable feature of the school environment, class rank. What are the long-run effects of a student’s ordinal rank in elementary school? Using administrative data on all public-school students in Texas, we show that students with a higher third-grade academic rank, conditional on achievement and classroom fixed effects, have higher subsequent test scores, are more likely to take AP classes, graduate from high school, enroll in and graduate from college, and ultimately have higher earnings 19 years later. We also discuss the necessary assumptions for the identification of rank effects and propose new solutions to identification challenges. The paper concludes by exploring the tradeoff between higher quality schools and higher rank in the presence of these rank-based peer effects.
Past research extensively documents inequalities in educational opportunity and achievement by students’ race/ethnicity or socioeconomic status (SES). Less scholarship focuses on how race/ethnicity and SES interact and jointly contribute to educational inequalities. We advance this burgeoning line of scholarship by charting math achievement trajectories and school socioeconomic composition by both student race/ethnicity and SES in California from 2014-15 through 2017-18. Linked administrative data allow us to operationalize student SES more richly than point-in-time free meal eligibility, a measure commonly used in education research. We find evidence of considerable racial/ethnic disparities in math achievement and school socioeconomic composition among same-SES students. White and Asian students score substantially higher on math achievement tests and attend higher-SES schools than same-SES Hispanic and Black students. Achievement and contextual inequalities are related: differential exposure to school SES by student race/ethnicity is associated with within-SES racial/ethnic achievement disparities. Our findings show that SES does not translate into the same contextual or achievement advantages for students of all racial/ethnic groups, demonstrating the importance of jointly considering student race/ethnicity and SES in future research and policy development.
A survey targeting education researchers conducted in November, 2020 provides both short- and longer-term predictions of how much achievement gaps between low- and high-income students in U.S elementary schools will change as a result of COVID-related disruptions to schooling and family life. Relative to a pre-COVID achievement gap of 1.00 SD, respondents’ median forecasts for increases in achievement gaps in elementary school by spring, 2021 were very large – from 1.00 to 1.30 and 1.25 SD, respectively, for math and reading. Researchers forecast only small reductions in gaps between spring 2021 and 2022. Although forecasts were heterogeneous, almost all respondents predicted that gaps would grow during the pandemic and would not return to pre-pandemic levels in the following school year. We discuss some implications of these predictions for strategies to reduce learning gaps exacerbated by the pandemic as well as the mental models researchers appear to employ in making their predictions.
Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers. Using nearly 1,000 word-to-word transcriptions of 4th- and 5th-grade English language arts classes, we apply novel text-as-data methods to develop automated measures of teaching to complement classroom observations traditionally done by human raters. This approach is free of rater bias and enables the detection of three instructional factors that are well aligned with commonly used observation protocols: classroom management, interactive instruction, and teacher-centered instruction. The teacher-centered instruction factor is a consistent negative predictor of value-added scores, even after controlling for teachers’ average classroom observation scores. The interactive instruction factor predicts positive value-added scores. Our results suggest that the text-as-data approach has the potential to enhance existing classroom observation systems through collecting far more data on teaching with a lower cost, higher speed, and the detection of multifaceted classroom practices.
In this paper we study the effects of three large, nearly-simultaneous coal-fired power plant closures on school absences in Chicago. We find that the closures resulted in a 7 percent reduction in absenteeism in nearby schools relative to those farther away following the closures. For the typical elementary school in our sample, this translates into around 372 fewer absence-days per year in the aggregate, or around 0.71 fewer annual absences per student. We find that reductions in absences were larger in schools where pre-closure exposure to coal-fired power plants was more intense: namely, schools with low levels of air conditioning, schools more frequently in the wind path of the plants, and non-magnet (i.e., neighborhood) schools where students were more likely to live nearby. To explore potential mechanisms responsible for these absence reductions we investigate the effects of the closures on housing values and children’s respiratory health. We do not find statistical evidence of endogenous migration into neighborhoods near the coal-fired power plants following the closures but do find declines in emergency department visits for asthma-related conditions among school-age children.
We study the effect of exposure to immigrants on the educational outcomes of US-born students, using a unique dataset combining population-level birth and school records from Florida. This research question is complicated by substantial school selection of US-born students, especially among White and comparatively affluent students, in response to the presence of immigrant students in the school. We propose a new identification strategy to partial out the unobserved non-random selection into schools, and find that the presence of immigrant students has a positive effect on the academic achievement of US-born students, especially for students from disadvantaged backgrounds. Moreover, the presence of immigrants does not affect negatively the performance of affluent US-born students, who typically show a higher academic achievement compared to immigrant students. We provide suggestive evidence on potential channels.
Despite calls for more evidence regarding the effectiveness of teacher education practices, causal research in the field remains rare. One reason is that we lack designs and measurement approaches that appropriately meet the challenges of causal inference in the context of teacher education programs. This article provides a framework for how to fill this gap. We first outline the difficulties of doing causal research in teacher education. We then describe a set of replicable practices for developing measures of key teaching outcomes, and propose causal research designs suited to the needs of the field. Finally, we identify community-wide initiatives that are necessary to advance effectiveness research in teacher education at scale.
The growing phenomenon of private tutoring has received minimal scholarly attention in the United States. We use 20 years of geocoded data on the universe of U.S. private tutoring centers to estimate the size and growth of this industry and to identify predictors of tutoring center locations. We document four important facts. First, from 1997-2016, the number of private tutoring centers grew steadily and rapidly, more than tripling from about 3,000 to nearly 10,000. Second, the number and growth of private tutoring centers is heavily concentrated in geographic areas with high income and parental education. Nearly half of tutoring centers are in areas in the top quintile of income. Third, even conditional on income and parental education, private tutoring centers tend to locate in areas with many immigrant and Asian-American families, suggesting important differences by nationality and ethnicity in demand for such services. Fourth, we see little evidence that prevalence of private tutoring centers is related to the structure of K-12 school markets, including the prevalence of private schools and charter or magnet school options. The rapid rise in high-income families’ demand for this form of private educational investment mimics phenomena observed in other spheres of education and family life, with potentially important implications for inequality in student outcomes.