Special Topics on Evaluation: Synthetic Control Methods
This course offers an introduction to synthetic control analysis, a relatively new method in the field of causal inference. The course is designed to provide a foundational understanding of when and why to use synthetic control methods, focusing on practical applications and hands-on examples using R.
Participants will begin with a brief overview of the synthetic controls concept, learning how these methods are employed to evaluate different types of outcome analyses. The course will cover two primary types of synthetic control methods:
- Single Treated Unit: Evaluating large aggregate units that have received treatment.
- Multiple Treated Units: Analyzing disaggregated control groups to assess treatment effects.
Speakers:
Gio Circo, Ph.D.
Gio Circo is a data scientist at Gainwell Technologies, where he is part of the Artificial Intelligence and Machine Learning team. His work primarily focuses on causal inference, Bayesian statistics, and anomaly detection. Before joining Gainwell Technologies, Gio was an Assistant Professor at the University of New Haven, where his research centered on gun violence, policing, and the fear of crime. He earned his Ph.D. in Criminal Justice from Michigan State University and holds an M.A. and a B.A. in Criminal Justice from Illinois State University.
Materials:
- Synthetic Controls Intro (9:22)
- R Practice Elective (15:49)
- Single and Multiple Treated Units (34:16)
- Code through example (1)
- Code through example (2)
- View slides