The Disciplinary Differences in the Characteristics and Effects of Non-Tenure-Track Faculty

Using data with detailed instructor employment information from a state college system, this study examines disciplinary variations in the characteristics and effects of non-tenure-track faculty hired through temporary and long-term employment. We identify substantial differences in demographic and employment characteristics between the two types of non-tenure-line faculty, where the differences are most pronounced in science, technology, engineering, mathematics, and health-related fields (STEM) at 4-year colleges. Using an instrumental variables strategy to address student sorting, our analyses indicate that taking introductory courses with temporary adjuncts reduces subsequent interest, and the effects are particularly large in STEM fields at 4-year colleges. Long-term non-tenure faculty are generally comparable with tenure-track faculty in student subsequent interest, but tenure-track faculty are associated with better subsequent performance in a handful of fields.

Accounting for Teacher Labor Markets and Student Segregation in Analyses of Teacher Quality Gaps

Studies show that historically underserved students are disproportionately assigned to less qualified and effective teachers, leading to a “teacher quality gap.” Past analyses decompose this gap to determine whether inequitable access is driven by teacher and student sorting across and within schools. These sorting mechanisms have divergent policy implications related to school finance, student desegregation, teacher recruitment, and classroom assignment. I argue that analyses of the teacher quality gap that consider how teachers and students are sorted across labor markets offer additional policy guidance. Using statewide data from Texas, I show that teacher quality gaps are driven by sorting across school districts within the same labor market, but this finding differs depending on how “teacher quality” is defined.

Measuring the Impacts of Teachers: Comment

Chetty, Friedman, and Rockoff (2014a, b) study value-added (VA) measures of teacher effectiveness. CFR (2014a) exploits teacher switching as a quasi-experiment, concluding that student sorting creates negligible bias in VA scores. CFR (2014b) finds VA scores are useful proxies for teachers' effects on students' long-run outcomes. I successfully reproduce each in North Carolina data. But I find that the quasi-experiment is invalid, as teacher switching is correlated with changes in student preparedness. Adjusting for this, I find moderate bias in VA scores, perhaps 10–35 percent as large, in variance terms, as teachers' causal effects. Long-run results are sensitive to controls and cannot support strong conclusions. (JEL H75, I21, J45)