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Educator labor markets
Economic downturns can cause major funding shortfalls for U.S. public schools, often forcing districts to make difficult budget cuts including teacher layoffs. In this brief, we synthesize the empirical literature on the widespread teacher layoffs caused by the Great Recession. Studies find that teacher layoffs harmed student achievement and were inequitably distributed across schools, teachers, and students. Research suggests that specific elements of the layoff process can exacerbate these negative effects. Seniority-based policies disproportionately concentrate layoffs among teachers of color who are more likely to be early career teachers. These “last-in first-out” policies also disproportionately affect disadvantaged students because these students are more likely to be taught by early career teachers. The common practice of widely distributing pink slips warning about a potential job loss also appears to increase teacher churn and negatively impact teacher performance. Drawing on this evidence, we outline a set of policy recommendations to minimize the need for teacher layoffs during economic downturns and ensure that the burden of any unavoidable job cuts does not continue to be borne by students of color and students from low-income backgrounds.
Over the last two decades, twenty-two states have moved away from traditional defined benefit (DB) pension systems and toward pension plan structures like the defined contribution (DC) plans now prevalent in the private sector. Others are considering such a reform as it is seen as a means of limiting future pension funding risk. It is important to understand the implications of such reforms for end-of-career exit patterns and workforce composition. Empirical evidence on the relationship between pension plan structure and retirement timing is currently limited, primarily because, most state pension reforms are so new that few employees enrolled in those alternative plans have reached retirement age. An exception, and the subject of our analysis, is the teacher retirement system in Washington State, which introduced a hybrid DB-DC plan in 1996 and allowed employees in its traditional DB plan to transfer into the new plan. Our analysis focuses on a years-of-service threshold, the crossing of which grants employees early retirement eligibility and, in many cases, a large upward shift in retirement wealth. The financial implications of crossing this threshold are far greater under the state’s traditional DB plan than under the hybrid plan. We find that employees are responsive to crossing the years-of-service threshold, but we fail to find significant evidence that the propensity to exit the workforce varies according to plan enrollment.
We estimate the education and earnings returns to enrolling in technical two-year degree programs at community colleges in Missouri. A unique feature of the Missouri context is the presence of a highly-regarded, nationally-ranked technical college: State Technical College of Missouri (State Tech). Compared to enrolling in a non-technical community college program, we find that enrolling in a technical program at State Tech greatly increases students’ likelihoods of graduation and earnings. In contrast, there is no evidence that technical education programs at other Missouri community colleges increase graduation rates, and our estimates of the earnings impacts of these other programs are much smaller than for State Tech. Our findings exemplify the importance of institutional differences in driving the efficacy of technical education and suggest great potential for high-quality programs to improve student outcomes.
A growing literature uses value-added (VA) models to quantify principals' contributions to improving student outcomes. Principal VA is typically estimated using a connected networks model that includes both principal and school fixed effects (FE) to isolate principal effectiveness from fixed school factors that principals cannot control. While conceptually appealing, high-dimensional FE regression models require sufficient variation to produce accurate VA estimates. Using simulation methods applied to administrative data from Tennessee and New York City, we show that limited mobility of principals among schools yields connected networks that are extremely sparse, where VA estimates are either highly localized or statistically unreliable. Employing a random effects shrinkage estimator, however, can alleviate estimation error to increase the reliability of principal VA.
We use publicly available, longitudinal data from Washington state to study the extent to which three interrelated processes—teacher attrition from the state teaching workforce, teacher mobility between teaching positions, and teacher hiring for open positions—contribute to “teacher quality gaps” (TQGs) between students of color and other students in K–12 public schools. Specifically, we develop and implement an agent-based model simulation of decisions about attrition, mobility, and hiring to assess the extent to which each process contributes to observed TQGs. We find that eliminating inequities in teacher mobility and hiring across different schools would close TQGs within 5 years, while just eliminating inequities in teacher hiring would close gaps within 10 years. On the other hand, eliminating inequities in teacher attrition without addressing mobility and hiring does little to close gaps.
Disparate turnover among teachers of color remains a persistent educational challenge, yet little research explores the link between school leadership, peer teaching staff, and turnover disparities. This study explores whether principal and peer teacher demographics predict teacher turnover in New York City, and whether they do so differently for teachers of color. We find teachers are less likely to exit when their principal and a higher share of peer teachers are of the same race/ethnicity, with Black teachers having especially lower transfer rates with a higher share of Black peer teachers. However, results suggest school leadership style and positive teacher relationships are not differentially associated with turnover for teachers of color. We conclude with a discussion of implications.
Many studies rely on public sector employees’ reported career intentions instead of measuring actual turnover, but research does not clearly document how these variables relate to one another. We develop and test three ways in which measures of employee intentions and turnover might relate to one another: (a) intention may measure the same underlying construct as turnover; (b) intention may be distinct from but strongly related to turnover; or (c) intentions may be distinct from turnover. Using nationally representative data on 102,970 public school teachers, we conduct a descriptive and regression analysis to probe how teachers’ turnover intentions are and are not associated with attrition. While there is some variation across measures of intent, we find evidence most consistent with the second scenario; intention is distinct from, but strongly related to, turnover. We offer recommendations for how researchers should use public sector employee intentions in research.
Strengthening teacher supply is a key policy objective for K–12 public education, but understanding of the early teacher pipeline remains limited. We leverage the universe of applications to a large public university in Texas from 2009–2020 to examine the pipeline into teacher education and employment as a K–12 public school teacher. A unique feature of Texas's centralized higher education application is it solicits potential interest in teacher certification. We document sharply declining interest in teaching over the period. Further, we show that nonwhite, male, and high-achieving students are substantially underrepresented in teacher education. Particularly for race/ethnicity, these disparities are only partially explained by differences in interest at application.
While investing in the teacher workforce is central to improving schools, school resources are notoriously limited, forcing school leaders to make difficult decisions on how to prioritize funds. This paper examines a critical input to resource allocation decisions: teacher preferences. Using an original, online discrete choice survey experiment with a national sample of 1,030 U.S. teachers, we estimate how much teachers value different features of a hypothetical teaching job. The findings show that (a) teachers value access to special education specialists, counselors, and nurses more than a 10% salary increase or 3-student reduction in class size, (b) investments in school counselors and nurses are strikingly cost-effective, as the value teachers alone place on each of these support roles far exceeds the per teacher cost of funding these positions, and (c) teachers who are also parents treat a 10% salary increase and a child care subsidy of similar value as near perfect substitutes. These novel estimates of teachers’ willingness to pay for student-based support professionals challenge the idea that inadequate compensation lies at the root of teacher workforce challenges and illustrate that reforms that exclusively focus on salary as a lever for influencing teacher mobility (e.g. transfer incentives) may be poorly aligned to teachers’ preferences.
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.