Job Market Paper
Instructor Value-added in Post-secondary Education (with Jacob Light and Anthony Yim)
Estimating post-secondary instructors’ value-added is challenging because college students select their courses and instructors. In the absence of sound measures of value-added, universities use subjective student evaluations to make personnel decisions. In this paper, we develop a method to estimate instructor value-added at any university. The method groups together students who have previously taken similar courses and estimates value-added based on differences in outcomes for students in the same group and same course who have different instructors. Using a unique policy at a large public university in Indiana, we show that our non-experimental method controls for selection just as well as methods that exploit conditional random assignment of students to courses. We next show that our method reduces forecast bias in a wider variety of institutions using data from nearly all public universities in Texas. We find that individual instructors matter for students’ future grades and post-college earnings in many subjects and courses. On average, moving to a 1 standard deviation better instructor would increase a student’s next semester GPA by 0.13 points, and earnings six years after college entry by 17%. Strikingly, value-added is only weakly correlated with student evaluations. An instructor retention policy based on value-added would result in 2.7% higher earnings for students attending Texas universities.
Publications
A Design-Based Perspective on Synthetic Control Methods (with Lea Bottmer, Guido Imbens, and Jann Spiess), Journal of Business & Economic Statistics, 2023 (alt link)
Why Have College Completion Rates Increased? (with Jeffrey T. Denning, Eric Eide, Kevin Mumford, and Rich Patterson), AEJ: Applied, 2023.
Divisibility Properties of Coefficients of Modular Functions in Genus Zero Levels (with Victoria Iba, and Paul Jenkins), Integers, 2019.
Working Papers
Easy A's, Less Pay: The Long-Term Effects of Grade Inflation (with Jeff Denning, Rachel Nesbit, and Nolan Pope)
Average grades continue to rise in the United States, raising the question of how grade inflation impacts students. We provide comprehensive evidence on how teacher grading practices affect students' long-run success. Using administrative high school data from Los Angeles and from Maryland that is linked to postsecondary and earnings records, we develop and validate two teacher-level measures of grade inflation: one measuring average grade inflation and another measuring a teacher's propensity to give a passing grade. These measures of grade inflation are distinct from teacher value-added, with grade inflating teachers having moderately lower cognitive value-added and slightly higher noncognitive value-added. These two measures also differentially impact students' long-term outcomes. Being assigned a higher average grade inflating teacher reduces a student's future test scores, the likelihood of graduating from high school, college enrollment, and ultimately earnings. In contrast, passing grade inflation reduces the likelihood of being held back and increases high school graduation, with limited long-run effects. The cumulative impact is economically significant: a teacher with one standard deviation higher average grade inflation reduces the present discounted value of lifetime earnings of their students by $213,872 per year.
Research in Progress
The Importance of Non-Major Courses in Predicting College Students' Post-Graduation Outcomes (with Jacob Light)
Performance-Based Funding and Grading Standards in Higher Education