My thesis consists of three chapters on the Economics of Education. In the first chapter, I take a structural approach to studying the extent to which teacher behavior and teacher interactions with students determine teaching contribution to test score growth in the classroom. Teachers’ contributions may differ across classrooms, as it may depend on the types of students taught and because teachers may adjust their effort to new contexts. The estimated model suggests that teacher and student efforts play a significant role in determining student knowledge. My findings indicate that teachers who are effective in teaching low-performing students may not be as effective in teaching high-performing students. In a counterfactual, I assigned teachers assessed as highly effective, according to value-added estimates, to classrooms with a high proportion of low-achieving students. The results suggest that the value-added measures overstate the expected performance of certain teachers in the reassigned classrooms. Additionally, I quantify the benefits of reassigning teachers based on their comparative advantages, effort choices, and endowments. Compared to the assignment based on the value-added specification, the new reassignment produces higher gains for the low-performing students. In my second chapter, I estimate the potential gains of paying teachers according to varying, optimally-designed linear schemes. The empirical literature considers a variety of schemes that have been evaluated under randomized controlled trials. However, there is little evidence about their relative performance. To better understand these mechanisms behind the schemes' performance, I use a publicly-available dataset from a teacher incentive experiment in Andhra Pradesh, India, containing both individual- and group-based piece-rate bonuses. I exploit the experimental nature of the data to test for the presence of peer pressure in the group-based scheme. I first document the existence of peer pressure in the group-based scheme, which mitigates free-rider incentives. Based on this result, I estimate the structural parameters of my model to recover the optimal incentive schemes that maximize the expected value of student achievement minus the expected payment to teachers. I find that an optimally designed group-based scheme could increase student academic achievement by about twice as much as the results obtained from an optimally designed individual-based incentive scheme. In my third paper, I study the impact that teachers may have on the academic performance of Black and Hispanic students, which I refer to as minority students. To do so, I estimate the distribution of matching effects between teachers and minority students. These matching effects capture the teachers' ability to reduce the achievement gap between their assigned students. Then, I study the relationship between the estimated matching effects and a set of teachers' characteristics and skills. This allows me to explore what type of teachers are better suited to teach minority students. I find that teachers can have a meaningful impact on their minority students' performance: a one-standard-deviation increase in the teacher matching effect generates achievement gains of 0.05 standard deviations. I do not find a relationship between the estimated matching effects and the teachers' race. However, I find that the matching effects are higher for teachers with better control of students' behavior. This evidence suggests that how teachers teach matters in improving minority students' performance.
Teacher Effectiveness, Educational Policy Design, Achievement Gaps, Optimal Contracts
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