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.

Using a large student-level dataset from a medium-sized regional comprehensive university, we measure the impact of taking an online prerequisite course on follow-up course grades. To control for self-selection into online courses, we utilize student, instructor, course, and time fixed effects augmented with an instrumental variable approach. We find that students’ grades in follow-up courses can be expected to be nearly one twelfth of a grade point lower if the prerequisite course was taken online. These results are robust to self-selection into online courses and into subsequent course enrollment.

The No Child Left Behind Act imposes sanctions on schools if the fraction of students demonstrating proficiency on a high-stakes test falls below a statewide pass rate. While the motivation behind this system is improved public school performance, it also provides incentives for schools to focus educational resources on the marginal student rather than those on the tails of the ability distribution. Using statewide, student-level panel data, students on the tails of the ability distribution, especially high-ability students, are demonstrated to score below expectations if their school is in danger from No Child Left Behind sanctions.