We study how the introduction of a rigorous teacher evaluation system in a large urban school district affects the quality composition of teacher turnovers. With the implementation of the new system, we document increased turnover among the least effective teachers and decreased turnover among the most effective teachers, relative to teachers in the middle of the distribution. Our findings demonstrate that the alignment between personnel decisions and teacher effectiveness can be improved through targeted personnel policies. However, the change in the composition of exiters brought on by the policy we study is too small to meaningfully impact student achievement.

Public school teachers retire much earlier than comparable professionals. Pension rule changes affecting new teachers can be used to close this gap in the long run, but any effects will not be observed for decades and the implications for workforce quality are unclear. This paper considers targeted incentive policies designed to deter retirement among senior, experienced high-need science and math teachers, as a policy to staff classrooms with qualified teachers and improve workforce quality. We use structural estimates from a dynamic retirement model to simulate the workforce effects of targeted late-career salary bonuses and deferred retirement plans (DROPs) using administrative data from Missouri. Although both policies produce additional teaching years at relatively low costs, by forcing teachers to reveal work–retirement preferences, DROPs generally yield incremental teacher years at lower cost per year. More generally, this work highlights the utility of using structural retirement models to analyze fiscal and workforce effects of changes to public sector pension plans, since the effects of pension rule changes cumulate over many years.

We compare teacher preparation programs in Missouri based on the effectiveness of their graduates in the classroom. The differences in effectiveness between teachers from different preparation programs are much smaller than has been suggested in previous work. In fact, virtually all of the variation in teacher effectiveness comes from within-program differences between teachers. Prior research has overstated differences in teacher performance across preparation programs by failing to properly account for teacher sampling.

During the late 1990s public pension funds across the United States accrued large actuarial surpluses. The seemingly flush conditions of the pension funds led legislators in most states to substantially improve retirement benefits for public workers, including teachers. In this study we examine the benefit enhancements to the teacher pension system in Missouri. The enhancements resulted in large windfall gains for teachers who were close to retirement when the legislation was enacted. By contrast, novice teachers, and teachers who had not yet entered the labor force, were made worse off. The reason is that front-end contribution rates have been raised for current teachers to offset past liabilities accrued from the enhancements. Total teacher retirement compensation, net of contribution costs, is lower for young teachers today as a result of the enhancement legislation. Given sharp increases in pension costs in other states, this finding may generalize to young teachers in many other plans.

Value-added modeling continues to gain traction as a tool for measuring teacher performance. However, recent research questions the validity of the value-added approach by showing that it does not mitigate student-teacher sorting bias (its presumed primary benefit). Our study explores this critique in more detail. Although we find that estimated teacher effects from some value-added models are severely biased, we also show that a sufficiently complex value-added model that evaluates teachers over multiple years reduces the sorting bias problem to statistical insignificance. One implication of our findings is that data from the first year or two of classroom teaching for novice teachers may be insufficient to make reliable judgments about quality. Overall, our results suggest that in some cases value-added modeling will continue to provide useful information about the effectiveness of educational inputs.

Value-added measures of teacher quality may be sensitive to the quantitative properties of the student tests upon which they are based. This article focuses on the sensitivity of value added to test score ceiling effects. Test score ceilings are increasingly common in testing instruments across the country as education policy continues to emphasize proficiency-based reform. Encouragingly, we show that over a wide range of test score ceiling severity, teachers' value-added estimates are only negligibly influenced by ceiling effects. However, as ceiling conditions approach those found in minimum-competency testing environments, value-added results are significantly altered. We suggest a simple statistical check for ceiling effects.