Summer Institute 2021 Methods Lectures: Causal Inference Using Synthetic Controls and Regression Discontinuity Designs

The credible estimation of causal effects is a central task of applied econometrics. Two tools for this purpose that have attracted growing interest in empirical research are regression discontinuity designs and synthetic control methods. The 2021 Methods Lectures, presented during the virtual Summer Institute by Alberto Abadie of MIT and NBER and Matias Cattaneo and Rocio Titiunik of Princeton University, introduce these tools and describe best practices for their application. A video recording of the three-part lecture series may be found above. Background papers and code for implementing some of these tools may be found here, and an archive of the 14 previous NBER Methods Lectures may be found here.

Supported by the Alfred P. Sloan Foundation