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EdWorkingPapers

Gautam Anand, Aishwarya Atluri, Lee Crawfurd, Todd Pugatch, Ketki Sheth.

Improving school quality in low and middle income countries (LMICs) is a global priority. One way to improve quality may be to improve the management skills of school leaders. In this systematic review, we analyze the impact of interventions targeting school leaders' management practices on student learning. We begin by describing the characteristics and responsibilities of school leaders using data from large, multi-country surveys. Second, we review the literature and conduct a meta-analysis of the causal effect of school management interventions on student learning, using 39 estimates from 20 evaluations. We estimate a statistically significant improvement in student learning of 0.04 standard deviations. We show that effect sizes are not related to program scale or intensity. We complement the meta-analysis by identifying common limitations to program effectiveness through a qualitative assessment of the studies included in our review. We find three main factors which mitigate program effectiveness: 1) low take-up; 2) lack of incentives or structure for implementation of recommendations; and 3) the lengthy causal chain linking management practices to student learning. Finally, to assess external validity of our review, we survey practitioners to compare characteristics between evaluated and commonly implemented programs. Our findings suggest that future work should focus on generating evidence on the marginal effect of common design elements in these interventions, including factors that promote school leader engagement and accountability.

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Ishtiaque Fazlul, Benjamin Scafidi.

During the Great Recession and in the years that immediately followed, previous research has well-documented that U.S. public school districts receiving larger shares of their funding from state governments experienced larger declines in expenditures per student, as the GR impacted state tax bases more than it impacted local tax bases. Using detailed financial data from the academic years 2004 to 2020, we analyze the longer-term effects of the GR on a broader array of U.S. public school district finances. Employing both difference-in-differences and event study approaches, our results indicate that public school expenditures and unspent end-of-year fund balances recovered and eventually exceeded pre-GR levels on an inflation-adjusted and per-student basis. However, the funding increases were heterogeneous such that districts receiving larger shares of funding from states were less successful at increasing spending and fund balances through 2020—more than ten years after the GR officially ended. Our empirical strategy survives a host of robustness checks. This pattern is concerning as more state-dependent districts tend to have higher proportions of disadvantaged students.

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Seth Gershenson, Constance A. Lindsay, Nicholas W. Papageorge, Romaine Campbell, Jessica H. Rendon.

The US teaching force remains disproportionately white while the student body grows more diverse. It is therefore important to understand how and under what conditions white teachers learn racial competency. This study applies a mixed-methods approach to investigate the hypothesis that Black peers improve white teachers’ effectiveness when teaching Black students. The quantitative portion of this study relies on longitudinal data from North Carolina to show that having a Black same-grade peer significantly improves the achievement and reduces the suspension rates of white teachers’ Black students. These effects are persistent over time and largest for novice teachers. Qualitative evidence from open-ended interviews of North Carolina public school teachers reaffirms these findings. Broadly, our findings suggest that the positive impact of Black teachers’ ability to successfully teach Black students is not limited to their direct interaction with Black students but is augmented by spillover effects on early-career white teachers, likely through peer learning.

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Mengyuan Liang.

Even though women have continuously caught up with men in education attainment and labor market participation since the 1970s, the wage gap between men and women still universally exists today. Do female college graduates still earn less than their male counterparts if men’s and women’s “profiles” of observed productivity-related characteristics are statistically adjusted to be equivalent? To answer this research question and better understand the current gender wage gap, I introduce a novel propensity score stratification method for gender wage gap decomposition. This new method overcomes certain limitations of the traditional Blinder-Oaxaca decomposition method, and provides an example of validly applying propensity score-based methods (mostly used in causal settings) to gender wage gap decomposition, a non-causal setting. Making use of this new method, I analyze a nationally representative sample from the Baccalaureate and Beyond Longitudinal Study, which represents the 1993 Cohort of U.S. college graduates. Through propensity score stratification, the observed productivity-related characteristics between men and women in the sample are statistically adjusted to be equivalent within each stratum of propensity score. After “equalizing” these characteristics, evidence shows the women-to-men wage ratio among this college educated population is still 87.4% at the tenth year after they graduated from college. This remaining gender gap cannot be explained by the observed gender differences in productivity-related characteristics, and is the evidence of a discriminatory wage gap possibly existing in the labor market. Additionally, the unexplained gender wage gap universally exists regardless whether these “profiles” of qualifications and labor market experience are stereotypically female or male. Even acknowledging that this research cannot account for all the gender differences in productivity due to data limitation, the results of this research will add to the empirical evidence of measuring the discriminatory wage gap that possibly exists in the labor market.

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Jinyong Hahn, John D. Singleton, Nese Yildiz.

Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for parameters of interest in this model under both strict and weak exogeneity assumptions. The key identification insight is that other periods' treatment variables are instruments for the unobserved fixed effects. We apply our proposed estimator to matched student-teacher data used to estimate value-added models of teacher quality. We show that the common assumption that the return to unobserved teacher quality is the same for all students is rejected by the data. We also present evidence that No Child Left Behind-era school accountability increased the effectiveness of teacher quality for lower performing students.

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Joshua Hyman.

Guidance counselors provide the main source of college advising for low-income high school students, but are woefully understaffed in high-need schools. This paper evaluates an approach to school-based college advising that relies on teachers rather than counselors. Using a randomized control trial in sixty-two Michigan high schools, I estimate the effects of a college planning course for high school seniors on postsecondary enrollment, persistence, and degree receipt. The course teaches about postsecondary education opportunities, application processes, and strategies for persisting toward a degree. I find no effect of the course on the number of students entering college, but an increase in the number persisting and earning a degree, particularly among low-income students. This is due to a shift in the composition of enrollees toward higher-achieving students: the course increases enrollment among high-achieving, low-income students, who have relatively high persistence rates, and reduces enrollment among low-achieving students, who in the course’s absence would have enrolled and then quickly dropped out. The program’s main cost is potential learning loss from displaced time in other subjects, which is difficult to measure but appears small.

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Syedah Aroob Iqbal, Harry Anthony Patrinos.

School closures induced by the COVID-19 pandemic led to concerns about student learning. This paper evaluates the effect of school closures on student learning in Uzbekistan, using a unique dataset that allows assessing change in learning over time. The findings show that test scores in math for grade 5 students improved over time by 0.29 standard deviation despite school closures. The outcomes among students who were assessed in 2019 improved by an average of 0.72 standard deviation over the next two years, slightly lower than the expected growth of 0.80 standard deviation. The paper explores the reasons for no learning loss.

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Torsten Figueiredo Walter, Guthrie Gray-Lobe, Sarah Kabay.

Hardware requirements are a barrier to widespread adoption of digital learning software among low-income populations. We investigate the demand among smallholder-farming households for a simple, adaptive math learning tool that can be accessed by widely available ``brick'' phones, and its effect on educational outcomes. Over a quarter of invited households used the tool, with greater demand among households lacking electricity, radios, or televisions. Usage was highest when schools were out of session. Engagement lapsed without regular reminders to use the service. Using random variation in access to the service, we find evidence that the platform increased test scores, school attendance, and grade attainment. Interpretation of these estimates is complicated by potentially endogenous outcome observation.

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Brendan Bartanen, Andrew Kwok, Andrew Avitabile, Brian Heseung Kim.

Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive paper examines preservice teachers' (PST) expressed motivation for pursuing a teaching career and its relationship with PST characteristics and outcomes. Using data from one of the largest teacher education programs in Texas, we use a natural language processing algorithm to categorize into topical groups roughly 2,800 essay responses to the prompt, "Explain why you decided to become a teacher.'' We identify 11 topics that largely reflect altruistic and intrinsic (though not extrinsic) reasons for teaching. The frequency of motivation topics varied substantially by PST gender, race/ethnicity, and certification area. While topics collectively explained little of the variance in PST outcomes, we found preliminary evidence that intrinsic enjoyment of teaching and prior experiences with adversity predicted higher performance during clinical teaching and lower attrition as a full-time K–12 teacher.

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John Westall, Amy Cummings.

Given the importance of early literacy to long-term student success, by 2021, 41 states and the District of Columbia adopted early literacy policies to improve student literacy by the end of third grade. We use an event-study approach to examine the impact of these policies on high- and low-stakes test scores. Our results suggest that adopting an early literacy policy improves elementary students’ reading achievement on high-stakes assessments, particularly in third grade and in states with comprehensive early literacy policies and third-grade retention requirements. We also find suggestive evidence that early literacy policies reduce socioeconomic and racial high-stakes achievement gaps in reading and have positive spillover effects on math achievement. However, we find little evidence of significant gains in low-stakes test scores except in states with comprehensive policies. Our findings highlight the importance of content and incentives for early literacy policies.

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