1. To what extent do teacher impacts on student outcomes vary across subgroups?
2. If so, how can incorporating these effects improve policy efficiency and equity?
Does student–teacher match quality exist? While prior research documents disparities in teachers’ impacts across student types, it has not distinguished between sorting and causal effects as the drivers of these disparities. I develop a flexible disparate value-added model (DVA) and introduce a novel measure of teacher quality—revealed comparative advantage (CA)—that captures the degree to which teachers affect student outcome gaps. Leveraging a quasi-experimental teacher turnover design, I show that the CA measure accurately predicts teachers’ disparate impacts: a teacher with a 1 standard deviation in black CA increases black students’ test scores by 1 standard deviation, with no effect on non-black students’ test scores. This methodological contribution offers a framework to study match effects, with implications for policy efficiency and equity.