Prior work on teacher candidates in Washington State has shown that about two thirds of individuals who trained to become teachers between 2005 and 2015 and received a teaching credential did not enter the state's public teaching workforce immediately after graduation, while about one third never entered a public teaching job in the state at all. In this analysis, we link data on these teacher candidates to unemployment insurance data in the state to provide a descriptive portrait of the future earnings and wages of these individuals inside and outside of public schools. Candidates who initially became public school teachers earned considerably more, on average, than candidates who were initially employed either in other education positions or in other sectors of the state's workforce. These differences persisted ten years into the average career and across transitions into and out of teaching. There is therefore little evidence that teacher candidates who did not become teachers were lured into other professions by higher compensation. Instead, the patterns are consistent with demand-side constraints on teacher hiring during this time period that resulted in individuals who wanted to become teachers taking positions that offered lower wages but could lead to future teaching positions.

We use longitudinal data from Massachusetts that link high school course-taking records in career and technical education (CTE) to postsecondary student outcomes to provide the first empirical evidence linking characteristics of CTE teachers to later student outcomes. We find that CTE teachers who received better scores on subject performance tests required for licensure tend to have students with higher longer-term earnings than CTE teachers who received lower scores on these tests, controlling for other factors. Specifically, we estimate that a 1 standard deviation increase in teacher performance on these tests is associated with about a $1,000 increase in average expected earnings for the teacher's students five years after their expected graduation date, controlling for licensure test area and observable differences between students.

A growing literature documents the importance of student teaching placements for teacher development. Emerging evidence from this literature highlights the importance of the mentor teacher who supervises this placement, as teachers tend to be more effective when they student teach with a mentor who is a more effective teacher. But the efficacy of policies that aim to have effective teachers serve as mentors depends a great deal on the availability of effective teachers to serve in this role. We therefore use data from Washington State to illustrate that there is ample scope for change in student teacher placements; in other words, there are far more effective teachers within fifty miles of a teacher education program (TEP) who could host a student teacher in each year than the number of teachers who serve in this role. We also discuss the considerable challenges to improvement efforts related to the need for better coordination between TEPs, K–12 school systems, and states. Finally, we argue that, if policy makers value teacher candidate development equivalently to teacher in-service development, they should be willing to pay substantially more than the current average compensation for mentor teachers to recruit effective teachers to serve in this role.

Over 2,000 teachers in the state of Washington received reduction-in-force (RIF) notices across the 2008–09 and 2009–10 school years. We link data on these RIF notices to an administrative data set that includes student, teacher, school, and district variables to determine the factors that predict the likelihood of a teacher receiving a RIF notice. Not surprisingly, we find that a teacher's seniority is the strongest predictor, but we also find (all else equal) that teachers with master's degrees and those credentialed in the high-need areas of math, science, and special education were less likely to receive a RIF notice. Value-added measures of teacher effectiveness, which can be calculated for a subset of the teachers, were not correlated with the probability of receiving a RIF notice. Finally, simulations suggest that a very different group of teachers would be targeted for layoffs under an effectiveness-based layoff scenario than under the seniority-driven system that exists today.