This working paper is a revised version of Josh Angrist’s recorded Nobel Memorial Lecture posted December 8, 2021.
The view that empirical strategies in economics should be transparent and credible now goes almost without saying. The local average treatment effects (LATE) framework for causal inference helped make this so. The LATE theorem tells us for whom particular instrumental variables (IV) and regression discontinuity estimates are valid. This lecture uses several empirical examples, mostly involving charter and exam schools, to highlight the value of LATE. A surprising exclusion restriction, an assumption central to the LATE interpretation of IV estimates, is shown to explain why enrollment at Chicago exam schools reduces student achievement. Angrist also makes two broader points: IV exclusion restrictions formalize commitment to clear and consistent explanations of reduced-form causal effects; compelling applications demonstrate the power of simple empirical strategies to generate new causal knowledge.
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