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At least sixteen US states have taken steps toward holding teacher preparation programs (TPPs) accountable for teacher value-added to student test scores. Yet it is unclear whether teacher quality differences between TPPs are large enough to make an accountability system worthwhile. Several statistical practices can make differences between TPPs appear larger and more significant than they are. We reanalyze TPP evaluations from 6 states—New York, Louisiana, Missouri, Washington, Texas, and Florida—using appropriate methods implemented by our new caterpillar command for Stata. Our results show that teacher quality differences between most TPPs are negligible—.01-.03 standard deviations in student test scores—even in states where larger differences were reported previously. While ranking all a state’s TPPs may not be possible or desirable, in some states and subjects we can find a single TPP whose teachers stand out as significantly above or below average. Such exceptional TPPs may reward further study.
Vocational education is formal education about work, and vocational programs of study typically target a narrow subset of middle-income occupations. In this chapter, we trace vocational education from competing 20th century education philosophies to its varied structures throughout the 21st century world. We then review the body of economic research on labor market returns to vocational education. Three themes from this rapidly expanding literature are that (1) workers with a vocational education tend to have a flatter age-employment profile than workers with an academic education, (2) individuals who seek and gain access to more secondary vocational education tend to have better attainment and early-career outcomes, whereas the effects of large-scale changes to tracking in secondary grades are more ambiguous; and (3) vocational postsecondary education is associated with improved labor market outcomes relative to no or incomplete postsecondary education, particularly for multi-year programs. We close by highlighting areas where more empirical research is needed, which include a deeper understanding of the long-term and inter-generational effects of vocational education on stability and growth in earnings, and the effects of vocational education in the developing world.
How are teacher pension benefits funded? Under traditional plans, the full cost of a career teacher’s benefits far exceeds the contributions designated for them. The gap between the two has three pieces, which may (with some license) be mnemonically tagged the three R’s of pension funding: Redistribution, Return, and Risk. First, some contributions made for the benefits of short-term teachers are Redistributed to fund the benefits of career teachers. Second, pension plans assume rosy Returns on their investments, which push costs onto future teachers and taxpayers. Finally, the Risk inherent in providing guaranteed pensions carries other costs, tangible and intangible, notably including the non-trivial risk of insolvency, which would dramatically raise mandated contributions and endanger future teacher benefits. I quantify these three components of the gap between benefits and contributions using the same metric as annual contributions. Illustrating with the California plan, I find the full cost of a career teacher’s annual accumulation of benefits can be as high as 46.6 percent of earnings, nearly triple the corresponding contributions of 17.5 percent. To understand this gap, which fiscally impacts all areas of education policy, researchers and practitioners may find it helpful to think of the three R’s of pension funding: Redistribution, Return, and Risk.
The estimation of test score “gaps” and gap trends plays an important role in monitoring educational inequality. Researchers decompose gaps and gap changes into within- and between-school portions to generate evidence on the role schools play in shaping these inequalities. However, existing decomposition methods assume an equal-interval test scale and are a poor fit to coarsened data such as proficiency categories. This leaves many potential data sources ill-suited for decomposition applications. We develop two decomposition approaches that overcome these limitations: an extension of V, an ordinal gap statistic, and an extension of ordered probit models. Simulations show V decompositions have negligible bias with small within-school samples. Ordered probit decompositions have negligible bias with large within-school samples but more serious bias with small within-school samples. More broadly, our methods enable analysts to (1) decompose the difference between two groups on any ordinal outcome into portions within- and between some third categorical variable, and (2) estimate scale-invariant between-group differences that adjust for a categorical covariate.
The opioid crisis is widely recognized as one of the most important public health emergencies of our time, and an issue that is particularly acute for rural communities. We propose a simple model of how opioids in a community can impact the education outcomes of children based on both the extent of exposure to opioids in the community and the child’s vulnerability to any given level of exposure. Next, we document the spatial dimensions of the intersection of the opioid crisis and standardized test scores using national data, with a focus on rural communities. Finally, we estimate the extent to which variation in one measure of the opioid crisis, drug-related mortality, is related to variation in test scores. We find strong relationships between the two, as well as evidence that the relationship is particularly salient for 3rd grade students in rural communities.
In this paper I study the impact of court-mandated school desegregation, which began in the late 1950s, on White individuals’ racial attitudes and politics in adulthood. Using geocoded nationwide data from the General Social Survey, I compare outcomes between respondents living in the same county who were differentially exposed to desegregated schools, based on respondent age and the year of court-mandated integration. With this differences-in-differences approach, I find that exposure to desegregated schools increased White individuals’ conservatism and negatively impacted their racial attitudes and support for policies promoting racial equity, such as affirmative action. Heterogeneity analyses indicate that effects are particularly pronounced in counties where opposition to integration was strongest: Southern counties desegregating after the passage of the Civil Rights Act of 1964 and counties where support for the Democratic presidential candidate between the 1960 and 1968 elections substantially decreased. My study provides causal evidence for key tenets of the contact hypothesis, which theorizes that Black-White contact in integrated schools can improve outgroup racial attitudes only under certain conditions, including when this intergroup contact has institutional support.
We explore how teachers unions affect education production by comparing outcomes between districts allocating new tax revenue amidst collective bargaining negotiations and districts allocating tax revenue well before. Districts facing union pressure increase teacher salaries and benefits, spend down reserves, and experience no student achievement gains. Conversely, districts facing less pressure hire more teachers (instead of increasing compensation) and realize significant student achievement gains. We interpret these results as causal evidence of the negative impact of teacher rent seeking on education production, as the timing of district tax elections relative to collective bargaining appears to be as good as random.
Many states have recently made or are considering changes to their teacher retirement systems. However, little is known about how teachers value various elements of their retirement benefits versus other aspects of their jobs and compensation. To help alleviate this gap, we use a discrete choice stated preferences experiment embedded in a nationally representative survey of teachers to estimate their willingness-to-pay for various retirement plan characteristics and other non-salary job components. We find that teachers would be indifferent between a traditional pension and alternative retirement plan designs if the alternatives were paired with 2 to 3 percent salary increases. Our results indicate that experience is a significant mediator of retirement plan preferences. While more experienced teachers are willing to pay more to keep their traditional pension plans, inexperienced teachers do not have strong preferences around retirement plan type. However, teachers’ willingness-to-pay for traditional pension plans is less than their willingness-to-pay for many other elements of their compensation, including the value of retirement benefits, retirement age, salary growth, healthcare coverage, and Social Security enrollment.
Virtual charter schools provide full-time, tuition-free K-12 education through internet-based instruction. Although virtual schools offer a personalized, content-appropriate experience, most research suggests these schools are negatively associated with achievement. Few studies account for differential rates of student mobility, which may produce biased estimates if mobility is jointly associated with virtual school enrollment and subsequent test scores. We account for student mobility in an evaluation of a single, large, anonymous virtual charter school. We estimate treatment effects of the virtual school on student achievement using a hybrid of exact and nearest-neighbor propensity score matching. Relative to their matched peers, we estimate that virtual students produce similar ELA scores and significantly worse math scores after one year. Among a limited sample of students observed for four years, we estimate that virtual students ultimately produce higher ELA scores and similar math scores relative to matched peers. We argue these findings are more reliable indicators of the independent effect of virtual schooling on student achievement because the match on student mobility is a proxy for otherwise unobservable negative selection factors.