Teacher turnover has adverse consequences for student achievement and imposes large financial costs for schools. Some have argued that high-stakes testing may lower teachers’ satisfaction with their jobs and could be a major contributor to teacher attrition. In this paper, we exploit changes in the tested grades and subjects in Georgia to study the effects of eliminating high-stakes testing on teacher turnover and the distribution of teachers across grades and schools. To measure the effect of testing pressures on teacher mobility choices we use a difference-in-differences approach, comparing changes in mobility over time in grades/subjects that discontinue testing vis-à-vis grades/subjects that are always tested. Our results show that eliminating testing did not have an impact on the likelihood of leaving teaching, moving between districts, changing schools within a district, or changing grades. Our findings hold for all teachers as well as for the subsample of early career teachers.

There is growing concern among policy makers over the quality of the teacher workforce in general, and the distribution of effective teachers across schools. The impact of teacher attrition on overall teacher quality will depend on the effectiveness of teachers who leave the profession. Likewise, teacher turnover may alleviate or worsen inequities in the distribution of teachers, depending on which teachers change schools or leave teaching and who replaces them. Using matched student–teacher panel data from the state of Florida, we examine teacher mobility across the distribution of effectiveness (as measured by teacher value added). We find that top-quartile and bottom-quartile teachers exit at a higher rate than do average-quality teachers. Additionally, as the share of peer teachers with more experience, advanced degrees, or professional certification increases, the likelihood of moving within-district decreases. We also find some evidence of assortative matching among teachers—more productive reading/language arts teachers are more likely to stay in teaching if they have more productive peer teachers.

We consider the challenges and implications of controlling for school contextual bias when modeling teacher preparation program effects. Because teachers are not randomly distributed across schools, failing to account for contextual factors in achievement models could bias preparation program estimates. Including school fixed effects controls for school environment by relying on differences among student outcomes within the same schools to identify the program effects, but this specification may be unidentified. Using statewide data from Florida, we examine whether the inclusion of school fixed effects is feasible, compare the sensitivity of the estimates to assumptions underlying for fixed effects, and determine what their inclusion implies about the precision of the preparation program estimates. We discuss the implications of our results on the feasibility, precision, and ranking of programs using the school fixed effect model for policy makers designing teacher preparation program evaluation systems.

The utility of value-added estimates of teachers' effects on student test scores depends on whether they can distinguish between high- and low-productivity teachers and predict future teacher performance. This article studies the year-to-year variability in value-added measures for elementary and middle school mathematics teachers from five large Florida school districts. We find year-to-year correlations in value-added measures in the range of 0.2–0.5 for elementary school and 0.3–0.7 for middle school teachers. Much of the variation in measured teacher performance (roughly 30–60 percent) is due to sampling error from “noise” in student test scores. Persistent teacher effects account for about 50 percent of the variation not due to noise for elementary teachers and about 70 percent for middle school teachers. The remaining variance is due to teacher-level time-varying factors, but little of it is explained by observed teacher characteristics. Averaging estimates from two years greatly improves their ability to predict future performance.

I utilize longitudinal data covering all public school students in Florida to study the performance of charter schools and their competitive impact on traditional public schools. Controlling for student-level fixed effects, I find achievement initially is lower in charters. However, by their fifth year of operation new charter schools reach a par with the average traditional public school in math and produce higher reading achievement scores than their traditional public school counterparts. Among charters, those targeting at-risk and special education students demonstrate lower student achievement, while charter schools managed by for-profit entities peform no differently on average than charters run by nonprofits. Controlling for preexisting traditional public school quality, competition from charter schools is associated with modest increases in math scores and unchanged reading scores in nearby traditional public schools.