Machine Learning for Treatment Effects and Structural Equation Models

The lecture series will provide a practical introduction to modern high-dimensional function fitting methods — a.k.a. machine learning (ML) methods — for efficient estimation and inference on treatment effects and structural parameters in empirical economic models. Participants will use R to allow them to immediately internalize and use the techniques in their own work. All lectures, except the introductory one, will be accompanied by R-code that can be used to reproduce the empirical examples in the lecture; there will be no gap between theory and practice.