July 29 – August 2, 2024

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.

Victor Chernozhukov works in econometrics and mathematical statistics, with much of recent work focusing on the quantification of uncertainty in very high dimensional models. He is a fellow of The Econometric Society and a recipient of The Alfred P. Sloan Research Fellowship and The Arnold Zellner Award. He was elected to the American Academy of Arts and Sciences in April 2016.

Application

The application deadline ended on April 15, 2024.

Admission and Registration

The Study Center communicates admission decision by the end of May, 2024, and sends participants the corresponding invoice. The registration form will be sent after the Center receives the payment of the course fee.