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Program and policy effects
We design a commitment contract for college students, "Study More Tomorrow," and conduct a randomized control trial testing a model of its demand. The contract commits students to attend peer tutoring if their midterm grade falls below a pre-specified threshold. The contract carries a financial penalty for noncompliance, in contrast to other commitment devices for studying tested in the literature. We find demand for the contract, with take-up of 10% among students randomly assigned a contract offer. Contract demand is not higher among students randomly assigned to a lower contract price, plausibly because a lower contract price also means a lower commitment benefit of the contract. Students with the highest perceived utility for peer tutoring have greater demand for commitment, consistent with our model. Contrary to the model's predictions, we fail to find evidence of increased demand among present-biased students or among those with higher self-reported tendency to procrastinate. Our results show that college students are willing to pay for study commitment devices. The sources of this demand do not align fully with behavioral theories, however.
We examine the dynamic nature of student-teacher match quality by studying the effect of having a teacher for more than one year. Using data from Tennessee and panel methods, we find that having a repeat teacher improves achievement and decreases absences, truancy, and suspensions. These results are robust to a range of tests for student and teacher sorting. High-achieving students benefit most academically and boys of color benefit most behaviorally. Effects increase with the share of repeat students in a class suggesting that classroom assignment policies intended to promote sustained student-teacher relationships such as looping may have even larger benefits.
Can public university honors programs deliver the benefits of selective undergraduate education within otherwise nonselective institutions? We evaluate the impact of admission to the Honors College at Oregon State University, a large nonselective public university. Admission to the Honors College depends heavily on a numerical application score. Nonlinearities in admissions probabilities as a function of this score allow us to compare applicants with similar scores, but different admissions outcomes, via a fuzzy regression kink design. The first stage is strong, with takeup of Honors College programming closely following nonlinearities in admissions probabilities. To estimate the causal effect of Honors College admission on human capital formation, we use these nonlinearities in the admissions function as instruments, combined with course-section fixed effects to account for strategic course selection. Honors College admission increases course grades by 0.10 grade points on the 0-4 scale, or 0.14 standard deviations. Effects are concentrated at the top of the course grade distribution. Previous exposure to Honors sections of courses in the same subject is a leading potential channel for increased grades. However, course grades of first-generation students decrease in response to Honors admission, driven by low performance in natural science courses. Results suggest that selective Honors programs can accelerate skill acquisition for high-achieving students at public universities, but not all students benefit from Honors admission.
A significant share of education and development research uses data collected by workers called “enumerators.” It is well-documented that “enumerator effects”—or inconsistent practices between the individual people who administer measurement tools— can be a key source of error in survey data collection. However, it is less understood whether this is a problem for academic assessments or performance tasks. We leverage a remote phone-based mathematics assessment of primary school students and survey of their parents in Kenya. Enumerators were randomized to students to study the presence of enumerator effects. We find that both the academic assessment and survey was prone to enumerator effects and use simulation to show that these effects were large enough to lead to spurious results at a troubling rate in the context of impact evaluation. We therefore recommend assessment administrators randomize enumerators at the student level and focus on training enumerators to minimize bias.
Knowing how policy-induced salary schedule changes affect teacher recruitment and retention will significantly advance our understanding of how resources matter for K-12 student learning. This study sheds light on this issue by estimating how legislative funding changes in Washington state in 2018-19—induced by the McCleary court-ordered reform—affected teacher salaries and labor market outcomes. By embedding a simulated instrumental variables approach in a mixed methods design, we observed that local collective bargaining negotiations directed new state-level funding allocations toward certificated base salaries, particularly among more senior teachers. Variability in political power, priorities, and interests of both districts and unions led to greater heterogeneity in teacher salary schedules. Teacher mobility rate was reduced in the first year of the reform, and subsequently new hiring rate was reduced in the second year. Suggestive evidence indicates that a $1,000 salary increase would have larger effects on junior teachers’ hiring and their transfers between districts to a greater extent than late-career teachers.
This study introduces the signal weighted teacher value-added model (SW VAM), a value-added model that weights student-level observations based on each student’s capacity to signal their assigned teacher’s quality. Specifically, the model leverages the repeated appearance of a given student to estimate student reliability and sensitivity parameters, whereas traditional VAMs represent a special case where all students exhibit identical parameters. Simulation study results indicate that SW VAMs outperform traditional VAMs at recovering true teacher quality when the assumption of student parameter invariance is met but have mixed performance under alternative assumptions of the true data generating process depending on data availability and the choice of priors. Evidence using an empirical data set suggests that SW VAM and traditional VAM results may disagree meaningfully in practice. These findings suggest that SW VAMs have promising potential to recover true teacher value-added in practical applications and, as a version of value-added models that attends to student differences, can be used to test the validity of traditional VAM assumptions in empirical contexts.
What guidance does research provide school districts about how to improve system performance and increase equity? Despite over 30 years of inquiry on the topic of effective districts, existing frameworks are relatively narrow in terms of disciplinary focus (primarily educational leadership perspectives) and research design (primarily qualitative case studies). To bridge this gap, we first review the theoretical literatures on how districts are thought to affect student outcomes, arguing that an expanded set of disciplinary perspectives—organizational behavior, political science, and economics—have distinct theories about why districts matter. Next, we conduct a systematic review of quantitative studies that estimate the relationship between district-level inputs and performance outcomes. This review reveals benefits of district-level policies that cross disciplinary perspectives, including higher teacher salaries and strategic hiring, lower student-teacher ratios, and data use. One implication is that future research on district-level policymaking needs to consider multiple disciplinary perspectives. Our review also reveals the need for significant additional causal evidence and provides a multidisciplinary map of theorized pathways through which districts could influence student outcomes that are ripe for rigorous testing.
We study the conditional gender wage gap among faculty at public research universities in the U.S. We begin by using a cross-sectional dataset from 2016 to replicate the long-standing finding in research that conditional on rich controls, female faculty earn less than their male colleagues. Next, we construct a data panel to track the evolution of the wage gap through 2021. We show that the gap is narrowing. It declined by more than 50 percent over the course of our data panel to the point where by 2021, it is no longer detectable at conventional levels of statistical significance.
The absence of federal support leaves undocumented students reliant on state policies to financially support their postsecondary education. We descriptively examine the postsecondary trajectories of tens of thousands of undocumented students newly eligible for California’s state aid program, using detailed application data to compare them to similar peers. In this context, undocumented students who apply and are eligible for the program use grant aid to attend college at rates similar to their peers. Undocumented students remain more likely to enroll in a community college at the expense of attending a broad access four-year college and have higher exit rates from two-year colleges. Yet undocumented students are equally likely to attend the more selective University of California system, and across four-year public colleges have persistence rates similar to their peers, showing that those who do attend four-year colleges perform well.
In spring 2020, nearly every U.S. public school closed at the onset of the Covid-19 pandemic. Existing evidence suggests that local political partisanship and teachers union strength were better predictors of fall 2020 school re-opening status than Covid case and death rates. We replicate and extend these analyses using data collected over the 2020-21 academic year. We demonstrate that Covid case and death rates were meaningfully associated with initial rates of in-person instruction. We also show that all three factors—Covid, partisanship, and teachers unions—became less predictive of in-person instruction as the school year continued. We then leverage data from two nationally representative surveys of Americans’ attitudes toward education and identify an as-yet undiscussed factor that predicts in-person instruction: public support for increasing teacher salaries. We speculate that education leaders were better able to manage the logistical and political complexities of school re-openings in communities with greater support for educators.