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Over the past three decades, children from low-income families and those from more affluent families have increasingly been attending different public schools. While recent work has helped us understand patterns of income segregation between districts and schools within districts, we know very little about segregation of students as they experience school: in the classroom. In this paper, we attempt to advance knowledge of trends in the segregation of students by income at the classroom level. We make use of detailed, student-level administrative data from North Carolina which provides a measure of a student’s free/reduced price lunch eligibility, which we refer to as economically disadvantaged (ED) status, along with information on classroom assignments. Since we know the ED status of each student in each classroom, we assess whether ED students are assigned to classes in the same pattern as other students or if are clustered/segregated into different classrooms. We know very little about the magnitude of income-based segregation, and almost nothing about whether this has changed over time, so we provide novel evidence on the question of whether segregation of students by socioeconomic status has increased within schools. We find that within-school segregation has risen by about 10 percent between 2007 and 2014 in elementary and middle schools we study. Further, we find that segregation of ED students within schools is correlated with the level of segregation between schools in districts, and this relationship grew stronger over our panel.
This study reports achievement levels and fall-to-spring gains in grades K to 8 for three groups of English Learners (ELs): (a) ever-ELs who were ever eligible for service; (b) current-ELs who continue to require service; and (b) dually-identified students eligible for both EL and Special Education services. I leverage unique data that include 186,139 ever-ELs and their never-EL peers in 1,520 schools. All three EL groups have lower mean math and reading achievement than the average of all students in kindergarten. Compared to the all-student average, ever-ELs and current-ELs make larger gains in the early grades but smaller gains in the middle grades. Dually-identified students make smaller gains than the all-student average across all grades in math and in kindergarten and 1st grade in reading. The expanding achievement gaps in the middle grades suggest better academic support is urgently needed for all multilingual students, especially dually-identified students.
We estimate the longer-run effects of attending an effective high school (one that improves a combination of test scores, survey measures of socio-emotional development, and behaviours in 9th grade) for students who are more versus less educationally advantaged (i.e., likely to attain more years of education based on 8th-grade characteristics). All students benefit from attending effective schools. However, the least advantaged students experience the largest improvements in high-school graduation, college-going, and school-based arrests. These patterns are driven by the least advantaged students benefiting the most from school impacts on the non-test-score dimensions of school quality. However, while there is considerable overlap in the effectiveness of schools attended by more and less advantaged students, it is the most advantaged students that are most likely to attend highly effective schools. These patterns underscore the importance of quality schools, and the non-test score components of quality schools, for improving the longer-run outcomes for less advantaged students.
Homelessness is rising among public school students in large cities across the US. Using nine years of student-level administrative data, we examine how homelessness affects students’ mathematics and attendance outcomes within the Los Angeles Unified School District, including the differential effects of homelessness based on duration and timing of their homeless experiences. Results using inverse probability of treatment weighting find that homeless students score 0.13 SD lower on math assessments and miss 5.8 additional days of school than students who never experience homeless. Results suggest that current homelessness has larger negative impacts on math achievement and attendance than former homelessness, and that transitory homelessness has larger negative impacts than persistent homelessness on the same outcomes.
Despite the significant influence that peer motivation is likely to have on educational investments during high school, it is difficult to test empirically since exogenous changes in peer motivation are rarely observed. In this paper, I focus on the 2012 introduction of Deferred Action for Childhood Arrivals (DACA) to study a setting in which peer motivation changed sharply for a subset of high school students. DACA significantly increased the returns to schooling for undocumented youth, while leaving the returns for their peers unchanged. I find that DACA induced undocumented youth to invest more in their education, which also had positive spillover effects on ineligible students (those born in the US) who attended high school with high concentrations of DACA-eligible youth. JEL Codes: I26, H52, J15
One of the controversies surrounding charter schools is whether these schools may either “cream skim” high-performing students from traditional public schools or “pushout” low-achieving students or students with discipline histories, leaving traditional public schools to educate the most challenging students. We use these terms strictly for brevity and acknowledge that many of the reasons that students are labeled high- or low-performing academically or behaviorally are beyond the control of the student. In this study, we use longitudinal statewide data from Tennessee and North Carolina and linear probability models to examine whether there is evidence consistent with these selective enrollment practices. Because school choice programs managed by districts (magnet and open enrollment programs) have a similar ability to cream skim and pushout students, we also examine these outcomes for these programs. Across the various school choice programs, magnet schools have the most evidence of cream skimming, but this might be expected as they often have selective admissions. For charter schools, we do not find patterns in the data consistent with cream skimming, but we do find evidence consistent with pushout behaviors based on discipline records. Finally, some have raised concerns that students may be pushed out near accountability test dates, but our results suggest no evidence consistent with this claim.
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.