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Between 2005 and 2016, international enrollment in US higher education nearly doubled. I examine how trade shocks in education affect public universities' decision-making. I construct a shift-share instrument to exploit institutions' historical networks with different origins of international students, income growth, and exchange-rate fluctuations. Contrary to claims that US-born students are crowded out, I find that international students increase schools' funding via tuition payments, which leads to increased in-state enrollment and lower tuition prices. Schools also keep steady per-student spending and recruit more students with high math scores. Lastly, states allocate more appropriations to universities that attract fewer international students.
Many public school diversity efforts rely on reassigning students from one school to another. While opponents of such efforts articulate concerns about the consequences of reassignments for students’ educational experiences, little evidence exists regarding these effects, particularly in contemporary policy contexts. Using an event study design, we leverage data from an innovative socioeconomic school desegregation plan to estimate the effects of reassignment on reassigned students’ achievement, attendance, and exposure to exclusionary discipline. Between 2000 and 2010, North Carolina’s Wake County Public School System (WCPSS) reassigned approximately 25 percent of students with the goal of creating socioeconomically diverse schools. Although WCPSS’s controlled school choice policy provided opportunities for reassigned students to opt out of their newly reassigned schools, our analysis indicates that reassigned students typically attended their newly reassigned schools. We find that reassignment modestly boosts reassigned students’ math achievement, reduces reassigned students’ rate of suspension, and has no offsetting negative consequences on other outcomes. Exploratory analyses suggest that the effects of reassignment do not meaningfully vary by student characteristics or school choice decisions. The results suggest that carefully designed school assignment policies can improve school diversity without imposing academic or disciplinary costs on reassigned students.
Numerous high-profile efforts have sought to “turn around” low-performing schools. Evidence on the effectiveness of school turnarounds, however, is mixed, and research offers little guidance on which models are more likely to succeed. We present a mixed-methods case study of turnaround efforts led by the Blueprint Schools Network in three schools in Boston. Using a difference-in-differences framework, we find that Blueprint raised student achievement in ELA by at least a quarter of a standard deviation, with suggestive evidence of comparably large effects in math. We document qualitatively how differential impacts across the three Blueprint schools relate to contextual and implementation factors. In particular, Blueprint’s role as a turnaround partner (in two schools) versus school operator (in one school) shaped its ability to implement its model. As a partner, Blueprint provided expertise and guidance but had limited ability to fully implement its model. In its role as an operator, Blueprint had full authority to implement its turnaround model, but was also responsible for managing the day-to-day operations of the school, a role for which it had limited prior experience.
We provide a descriptive analysis of within-school and neighborhood similarity in high school applications in New York City. We depart from prior work by examining similarity in applications to specific schools rather than preferences for school characteristics. We find surprisingly low similarity within schools and neighborhoods, but substantial variation by race and prior achievement. White and Asian students are more likely to have choices in common relative to Black and Hispanic students, a difference that persists after controlling for achievement and location. Likewise, higher-achieving students are more likely to have choices in common, conditional on other student characteristics and location. An implication is that students’ likelihood of attending high school without any peers from their middle school or neighborhood varies by student background.
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.
Virtual charter schools provide full-time, tuition-free K-12 education through internet-based instruction. Although virtual schools offer a personalized learning experience, most research suggests these schools are negatively associated with achievement. Few studies account for differential rates of student mobility, which may produce biased estimates if mobility is jointly associated with virtual school enrollment and subsequent test scores. We evaluate the effects of a single, large, anonymous virtual charter school on student achievement using a hybrid of exact and nearest-neighbor propensity score matching. Relative to their matched peers, we estimate that virtual students produce marginally worse ELA scores and significantly worse math scores after one year. When controlling for student mobility during the outcome year, estimates of virtual schooling are slightly less negative. These findings may be more reliable indicators of the independent effect of virtual schooling if matching on mobility proxies for otherwise unobservable negative selection factors.
One of the controversies surrounding charter schools is whether these schools may either “cream skim” high-performing students from traditional public schools or “pushout” low-achieving students or students with discipline histories, leaving traditional public schools to educate the most challenging students. We use these terms strictly for brevity and acknowledge that many of the reasons that students are labeled high- or low-performing academically or behaviorally are beyond the control of the student. In this study, we use longitudinal statewide data from Tennessee and North Carolina and linear probability models to examine whether there is evidence consistent with these selective enrollment practices. Because school choice programs managed by districts (magnet and open enrollment programs) have a similar ability to cream skim and pushout students, we also examine these outcomes for these programs. Across the various school choice programs, magnet schools have the most evidence of cream skimming, but this might be expected as they often have selective admissions. For charter schools, we do not find patterns in the data consistent with cream skimming, but we do find evidence consistent with pushout behaviors based on discipline records. Finally, some have raised concerns that students may be pushed out near accountability test dates, but our results suggest no evidence consistent with this claim.
We conduct a comprehensive examination of the causal effect of charter schools on school segregation, using a triple differences design that utilizes between-grade differences in charter expansion within school systems, and an instrumental variable approach that leverages charter school opening event variation. Charter schools increase school segregation for Black, Hispanic, White, and Asian students. The effect is of modest magnitude; segregation would fall 6 percent were charter schools eliminated from the average district. Analysis across varied geographies reveals countervailing forces. In metropolitan areas, charters improve integration between districts, especially in areas with intense school district fragmentation.
Evidence on educational returns and the factors that determine the demand for schooling in developing countries is extremely scarce. We use two surveys from Tanzania to estimate both the actual and perceived schooling returns and subsequently examine what factors drive individual misperceptions regarding actual returns. Using ordinary least squares and instrumental variable methods, we find that each additional year of schooling in Tanzania increases earnings, on average, by 9 to 11 percent. We find that on average, individuals underestimate returns to schooling by 74 to 79 percent, and three factors are associated with these misperceptions: income, asset poverty, and educational attainment. Shedding light on what factors relate to individual beliefs about educational returns can inform policy on how to structure effective interventions to correct individuals' misperceptions.
COVID-19 has forced essentially all schools in the country to close their doors to inperson activities. In this study, we provide new evidence about variation in school responses across school types. We focus on five main constructs of school activity during COVID-19: personalization and engagement in instruction, personalization and engagement in other school communication with students, progress monitoring (especially assignment grading), breadth of services (e.g., counseling and meals), and equitable access (to technology and services for students with special needs). We find that the strongest predictor of the extent of school activities was the education level of parents and other adults in schools’ neighborhoods. Internet access also predicts school responses. Race, parent/adult income, and school spending do not predict school responses. Private schools shifted to remote learning several days faster than traditional public schools, though others eventually caught up. On some measures, charter schools exceeded the responses of other schools; in other cases, traditional public schools had the highest overall measures. States in the Midwest responded more aggressively than those in other regions, especially the South, even after controlling for the full set of additional covariates. Learning management systems were reported by a large majority of schools, followed by video communication tools and tutorial/assessment programs. Several methods are proposed and implemented to address differential website use. We discuss potential implications of these findings for policy and effects on student outcomes.