Causal Inference III - Starting April 26th

Causal Inference III. April 26th and 27th
Full Schedule: https://www.mixtapesessions.io/session/ci_III_apr26
About this Event

Workshop description:

Synthetic control has been called the most important innovation in causal inference of the last two decades (Athey and Imbens 2018). It's use has been seen across the social sciences but even industry and government agencies. The method combines many design elements from unconfoundedness principles to difference-in-differences estimation to help find suitable estimates of counterfactuals in panel settings. Each day is 8 hours with 15 minute breaks on the hour plus an hour for lunch. We will review the theory behind several estimators, go into detail on the intuition of the estimation strategies and identification itself, as well as explore code in R and Stata and applications using these methods. The goal as always is that participants leave the workshop with competency and confidence. This class will be a sequel to the Causal Inference I and II.

Daily Structure:

This is a 2-day workshop. The goal of the workshop is for students to gain enough knowledge from the lectures and experience from the programming activities that they become confident and capable enough to implement and interpret these methods in their own work, as well as continue to learn this new material on their own after the workshop concludes. Each day lasts 8 hours with lectures and “coding together” sessions.

About the instructor:

Scott Cunningham is a professor of economics at Baylor University in Waco Texas. He has published in economics outlets such as The Review of Economic Studies, Journal of Urban Economics, Journal of Human Resources, Journal of Public Economics, Journal of Development Economics and more. He is the author of Causal Inference: the Mixtape published by Yale University Press in 2021 and co-editor of The Handbook on the Economics of Prostitution (with Manisha Shah) published by Oxford University Press in 2016. His research focus covers a range of applied topics in health and labor, including sex work, abortion, drug policy and mental healthcare. He has taught dozens of in-person and online workshops on causal inference and difference-in-differences to universities and firms across the world including Facebook, HP, University of Oxford, London School of Economics, University of Pennsylvania and many more.

International and Student Pricing:

Email [email protected] for student and international pricing.