Replication Data for: Measuring the Impacts of Teachers: (I) Evaluating Bias in Teacher Value-Added Estimates; (II) Teacher Value-Added and Student Outcomes in Adulthood

This dataset contains replication files for \"Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates\" and \"Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood\" by Raj Chetty, John Friedman, and Jonah E. Rockoff. For more information, see https://opportunityinsights.org/paper/teachersi/ and https://opportunityinsights.org/paper/teachersii/. A summary of each related publication follows. I: Are teachers’ impacts on students’ test scores (“value-added”) a good measure of their quality? One reason this question has sparked debate is disagreement about whether value-added (VA) measures provide unbiased estimates of teachers’ causal impacts on student achievement. We test for bias in VA using previously unobserved parent characteristics and a quasi-experimental design based on changes in teaching staff. Using school district and tax records for more than one million children, we find that VA models which control for a student’s prior test scores exhibit little bias in forecasting teachers’ impacts on student achievement. II: Are teachers’ impacts on students’ test scores (“value-added”) a good measure of their quality? This question has sparked debate partly because of a lack of evidence on whether high value-added (VA) teachers improve students’ long-term outcomes. Using school district and tax records for more than one million children, we find that students assigned to high-VA teachers are more likely to attend college, earn higher salaries, and are less likely to have children as teenagers. Replacing a teacher whose VA is in the bottom 5% with an average teacher would increase the present value of students’ lifetime income by approximately $250,000 per classroom.