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Program and policy effects

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We extend teacher evaluation research by estimating a reformed evaluation system's plausibly causal average effects on rural student achievement, identifying the settings where evaluation works, and incorporating evaluation expenditures. That the literature omits these contributions is concerning as research implies it hinders evidence-based teacher evaluation policymaking for rural districts, which outnumber urban districts. We apply a difference-in-differences framework to Missouri administrative data. Missouri districts could design and maintain reformed systems or outsource these tasks for a small fee to organizations like the Network for Educator Effectiveness (NEE), an evaluation system created for rural users. NEE does not affect student achievement on average but it improves math, and possibly reading, achievement in rural schools where the average student's prior-year achievement score is below the state average or the average teacher's years of experience are below the state average.

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The landscape of developmental education has experienced significant shifts over the last decade nationwide, as more than 20 states and higher education systems have transitioned from the traditional prerequisite model to corequisite remediation. Drawing on administrative data from Tennessee community colleges from 2010 to 2020, this study examined the heterogeneous effects of corequisite reform for remediation-eligible students with varying levels of academic preparation. Using difference-in-differences and event study designs, we found that corequisite remediation significantly improved gateway and subsequent college-level course completion for students in all placement test score groups below the college-level threshold. For math, the positive effects on college-level course completion were stronger for higher-scoring remedial students than for those with lower placement test scores, whereas the pattern was reversed for English. However, since the corequisite reform, students requiring remediation were more likely to drop out of the public college system, and those with the lowest scores were less likely to earn short-term certificates.

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Umut Özek.

Public policies targeting individuals based on need often impose disproportionate burden on communities that lack the resources to implement these policies effectively. In an elementary school setting, I examine whether community-level interventions focusing on similar needs and providing resources to build capacity in these communities could improve outcomes by improving the effectiveness of individual-level interventions. I find that the extended school day policy that targets lowest-performing schools in reading in Florida significantly improved the effectiveness of the third-grade retention policy in these schools. These complementarities were large enough to close the gap in retention effects between targeted and higher-performing schools.

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To understand the causes and consequences of polarized demand for government expenditure, we conduct three field experiments in the context of public higher education. The first two experiments study polarization in taxpayer demand. We provide information to shape beliefs about social returns on investment. Our treatments narrow the political partisan gap in ideal policies---a reduction in ideological polarization---by up to 32%, with differences in partisan reasoning as a key mechanism. Providing information also affects how people communicate their ideal policies to elected officials, increasing their propensity to write a (positive) letter to an official of the other party---a reduction in affective polarization. In the third experiment, we send these letters to a randomized subset of elected officials to study how policymakers respond to constituent demand. We find that officials who receive their constituents' demands engage more with higher education issues in our correspondences.

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High-impact tutoring has emerged as a primary school district investment for addressing learning loss that occurred during the COVID-19 pandemic. While existing research shows that high-impact tutoring is effective for accelerating student learning, this study examined the school-level facilitators and barriers to scaling high-impact tutoring. Situated in an urban traditional school district and an urban charter management organization, we collected survey and interview data from teachers and administrators to identify scaling challenges. Major barriers to scaling included time and space constraints, tutor supply and quality, updated data systems, and school level costs, while a key facilitator was teacher buy-in. We end the paper with recommendations for how districts can strategically grow their high-impact tutoring efforts.

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In recent years, several states have expanded a new publicly funded learning option: Transitional Kindergarten (TK). TK programs bridge prekindergarten and kindergarten in their eligibility, requirements, and design. We use Michigan’s TK program as a case study on the fit of this new entrant in the early learning landscape. Michigan’s program is well suited for this purpose because it contains most of the research-aligned program design elements of other large-scale TK programs across the country. Using statewide administrative data, we describe which districts offer TK when doing so is optional, the characteristics of children who enroll in TK at four and five years old, and substitution patterns between TK and alternative learning options. Broadly, we find TK in Michigan closes some socioeconomic gaps in early program enrollment while exacerbating others. Specifically, districts with larger proportions of White students and smaller proportions of economically disadvantaged students are more likely to offer TK than other districts. Within districts that do not offer TK in every school, TK is targeted to schools with more economically disadvantaged students. Among preschool-age children, those from non-economically disadvantaged families are more likely to enroll in TK than their peers; among kindergarten-age children, there is little difference in take-up by family income. Finally, we find evidence of substitution, with some children enrolling in TK instead of state-funded prekindergarten or instead of enrolling in kindergarten early, though with no evidence that public slots decline overall. Our findings have implications for addressing the fragmented early education landscape when expanding programs.

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We study how colleges shape their students' voting habits by linking millions of SAT takers to their college-enrollment and voting histories. To begin, we show that the fraction of students from a particular college who vote varies systematically by the college's attributes (e.g. increasing with selectivity) but also that seemingly similar colleges can have markedly different voting rates. Next, after controlling for students' college application portfolios and pre-college voting behavior, we find that attending a college with a 10 percentage-point higher voting rate increases entrants' probability of voting by 4 percentage points (10 percent). This effect arises during college, persists after college, and is almost entirely driven by higher voting-rate colleges making new voters. College peers' initial voting propensity plays no discernible role.

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We examine the fundamental and complex role that time plays in the learning process. We begin by developing a conceptual framework to elucidate the multiple obstacles schools face in converting total time in school into active learning time. We then synthesize the causal research and document a clear positive effect of additional time on student achievement typically of small to medium magnitude depending on dosage, use, and context. Further descriptive analyses reveal how large differences in the length of the school day and year across public schools are an underappreciated dimension of educational inequality in the United States. Finally, our case study of time loss in one urban district demonstrates the potential to substantially increase instructional time within existing constraints.

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Blake Heller.

In 2016, the GED® introduced college readiness benchmarks designed to identify testers who are academically prepared for credit-bearing college coursework. The benchmarks are promoted as awarding college credits or exempting “college-ready” GED® graduates from remedial coursework. I show descriptive evidence that those identified as college-ready by these benchmarks enroll and persist in college at significantly higher rates than others who pass the GED® exam, but at lower rates than recent graduates with traditional high school diplomas. Regression discontinuity estimates show that crossing a college readiness threshold does not substantially influence testers' college enrollment or persistence during the two years following their first test attempt. Relatedly, I observe little exam retaking by those who fall narrowly short of the minimum college readiness score thresholds. This contrasts strongly with retaking behavior near the lower GED® passing threshold that determines eligibility for a high school equivalency credential. Those who narrowly fail a GED® subject test are over 100 times more likely to retest than those who fall just short of a college readiness benchmark in the same subject. GED® college readiness benchmarks do not currently appear to promote better college outcomes, but in the absence of more detailed test score information they offer a simple heuristic to predict short-run college enrollment and persistence among GED® graduates, particularly for those who identify educational gain as a primary reason for testing. The results highlight the promise and challenges associated with building pathways for non-traditional students to earn credit for prior learning.

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We use a marginal treatment effect (MTE) representation of a fuzzy regression discontinuity setting to propose a novel estimator. The estimator can be thought of as extrapolating the traditional fuzzy regression discontinuity estimate or as an observational study that adjusts for endogenous selection into treatment using information at the discontinuity. We show in a frequentest framework that it is consistent under weaker assumptions than existing approaches and then discuss conditions in a Bayesian framework under which it can be considered the posterior mean given the observed conditional moments. We then use this approach to examine the effects of early grade retention. We show that the benefits of early grade retention policies are larger for students with lower baseline achievement and smaller for low-performing students who are exempt from retention. These findings imply that (1) the benefits of early grade retention policies are larger than have been estimated using traditional fuzzy regression discontinuity designs but that (2) retaining additional students would have a limited effect on student outcomes.

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