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We study the combined effects of charter schools, and their various mechanisms, on a national level and across multiple outcomes. Using difference-in-differences and fixed effects methods, we find that charter entry (above 10 percent market share) increases high school graduation rate in geographic districts by about 2-4 percentage points and increases test scores by 0.06-0.16 standard deviations. Charter effects peak with 5-15 percent charter market share. Also, total effects are comprised not only of participant and competitive effects, but also the charter-induced closure of low-performing traditional public schools. The analysis addresses potential endogeneity of charter school location and timing.
We study whether reallocating existing teachers across schools within a district can increase student achievement, and what policies would help achieve these gains. Using a model of multi-dimensional value-added, we find meaningful achievement gains from reallocating teachers within a district. Using an estimated equilibrium model of the teacher labor market, we find that achieving most of these gains requires directly affecting teachers' preferences over schools. In contrast, directly affecting principals' selection of teachers can lower student achievement. Our analysis highlights the importance of equilibrium and second-best reasoning in analyzing teacher labor market policies.
We study a California policy that loosened constraints on some local governments by lowering the share of votes required to pass school capital improvement bond referendums. We show that the policy change yielded larger tax proposals that received less support from voters, yet led to a doubling of approved spending. We show that this effect is concentrated in more racially diverse jurisdictions and that loosening these electoral constraints completely closed the gap in funding between these areas. We develop an agenda-setter model of the interaction between local government officials and voters to illustrate potential mechanisms behind these results.
Dual-enrollment courses are theorized to promote students' preparedness for college in part by bolstering their beneficial beliefs, such as academic self-efficacy, educational expectations, and sense of college belonging. These beliefs may also shape students' experiences and outcomes in dual-enrollment courses, yet few if any studies have examined this possibility. We study a large dual-enrollment program created by a university in the Southwest to examine these patterns. We find that mathematics self-efficacy and educational expectations predict performance in dual-enrollment courses, even when controlling for students' academic preparedness, while factors such as high school belonging, college belonging, and self-efficacy in other academic domains are unrelated to academic performance. However, we also find that students of color and first-generation students tend to have lower self-efficacy and educational expectations before enrolling in dual-enrollment courses, in addition to having lower levels of academic preparation. These findings suggest that students from historically marginalized populations may benefit from social-psychological as well as academic supports in order to receive maximum benefits from early postsecondary opportunities such as dual-enrollment. Our findings have implications for how states and dual-enrollment programs determine eligibility for dual-enrollment as well as how dual-enrollment programs should be designed and delivered in order to promote equity in college preparedness.
This paper reports the results of a large, school-level randomized controlled trial evaluating a set of three informational interventions for young people choosing high schools in 473 middle schools, serving over 115,000 8th graders. The interventions differed in their level of customization to the student and their mode of delivery (paper or online); all treated schools received identical materials to scaffold the decision-making process. Every intervention reduced likelihood of application to and enrollment in schools with graduation rates below the city median (75 percent). An important channel is their effect on reducing nonoptimal first choice application strategies. Providing a simplified, middle-school specific list of relatively high graduation rate schools had the largest impacts, causing students to enroll in high schools with 1.5-percentage point higher graduation rates. Providing the same information online, however, did not alter students’ choices or enrollment. This appears to be due to low utilization. Online interventions with individual customization, including a recommendation tool and search engine, induced students to enroll in high schools with 1-percentage point higher graduation rates, but with more variance in impact. Together, these results show that successful informational interventions must generate engagement with the material, and this is possible through multiple channels.
The COVID-19 pandemic has been a seismic and on-going disruption to K-12 schooling. Using test scores from 5.4 million U.S. students in grades 3-8, we tracked changes in math and reading achievement across the first two years of the pandemic. Average fall 2021 math test scores in grades 3-8 were .20-27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores decreased by .09-.18 SDs. Achievement gaps between students in low-poverty and high-poverty elementary schools grew by .10-.20 SDs, primarily during the 2020-21 school year. Observed declines are more substantial than during other recent school disruptions, such as those due to natural disasters.
We develop a new framework for identifying at-risk students in public schools. Our framework has two fundamental advantages over status quo systems: (1) it is based on a clear definition of what it means for a student to be at risk and (2) it leverages states’ rich administrative data systems to produce more informative risk measures. Our framework is more effective than common alternatives at identifying students who are at risk of low academic performance and we use policy simulations to show that it can be used to target resources toward these students more efficiently. It also offers several other benefits relative to status quo systems. We provide an alternative approach to risk measurement that states can use to inform funding, accountability, and other policies, rather than continuing to rely on broad categories tied to the nebulous concept of “disadvantage.”
We explore the dynamics of competitive search in the K-12 public education sector. Using data from Boston Public Schools, we document how teacher labor supply varies substantially by position types, schools, and the timing of job postings. We find that early-posted positions are more likely to be filled and end up securing new hires that are better-qualified, more-effective, and more likely to remain at a school. In contrast, the number of applicants to a position is largely unassociated with hire quality, suggesting that schools may struggle to identify and select the best candidates even when there is a large pool of qualified applicants. Our findings point to substantial unrealized potential for improving teacher hiring.
School closures induced by COVID-19 placed heightened emphasis on alternative ways to measure student learning besides in-person exams. We leverage the administration of phone-based assessments (PBAs) measuring numeracy and literacy for primary school children in Kenya, along with in-person standardized tests administered to the same students prior to school shutdowns, to assess the validity of PBAs. Compared to repeated in-person assessments, PBAs did not severely misclassify students’ relative performance, but PBA scores did tend to be further from baseline in-person scores than repeated in-person assessments from each other. As such, PBAs performed well at measuring aggregate but not individual learning levels. Administrators can therefore use these tools for aggregate measurement, such as in the context of impact evaluation, but be wary of PBAs for individual-level tracking or high-stakes decisions. Results also reveal the importance of making deliberate efforts to reach a representative sample and selecting items that provide discriminating power.
Families and governments are the primary sources of investment in children, proving access to basic resources and other developmental opportunities. Recent research identifies significant class gaps in parental investments that contribute to high levels of inequality by family income and education and, potentially, to inequality in children’s development. State-level public investments in children and families have the potential to reduce class inequality in children’s developmental environments by affecting parents’ behavior. Using newly assembled administrative data from 1998-2014, linked to household-level data from the Consumer Expenditure Survey, we examine how public sector investment in income support, health and education is associated with the private expenditures of low and high-SES parents on developmental items for children. Are class gaps in parental investments in children narrower in contexts of higher public investment for children and families? We find that more generous public spending for children and families is associated with significantly narrower class gaps in private parental investments. Moreover, we find that equalization is driven by bottom up increases in low-SES household spending for the progressive investments of income support and health, and by top down decreases in high-SES household spending for the universal investment of public education.