AEM 6121
Applied Econometrics II
The goal of the course is to provide graduate students with frontier econometric tools for conducting empirical research. We will cover prominent methods for causal inference, including randomized experiments, difference-in-difference, regression discontinuity, synthetic control, shift-share, matching, and statistical sensitivity tests. The course will also cover machine learning for prediction and variable selection, and selected topics in time series econometrics.
Topics
- Apply core econometric tools for causal inference in secondary data, including difference-in-difference, regression discontinuity, shift-share, synthetic control, and matching.
- Interpret and critically evaluate experimental research on the economic and social impacts of specific policies and programs.
- Apply machine learning tools for prediction and variable selection.
- Apply time series econometrics techniques to the analysis of one or more variables.
- Replicate the analysis in a recent publication or high quality working pap er that applies one or more of the causal inference tools covered in this course.
Official roster learning outcomes
Prerequisites & course information
AEM 6120 or equivalent.
Sources
- Course catalogue ↗2026-2027