Slides for AIDE Lab undergraduate internship training in Data Analysis and Applied Economics at the University of Arizona, adapted from @NickCH-K class on Causal Inference at Seattle University.
This internship training follows The Effect: An Introduction to Research Design and Causality, all of which is currently available online.
Lecture 1: Describing Variables
Lecture 1: Describing Variables COVID Examples
Lecture 2: Describing Relationships
Lecture 5: Drawing Causal Diagrams
Lecture 6: Causal Paths & Closing Back Doors
Lecture 6b: Estimating Fixed Effects
[Lecture 7: Finding Front Doors]
[Lecture 7b: Event Study Methods]
[Lecture 8: Treatment Effects]
[Lecture 8b: Difference-in-Differences Estimation]
[Lecture 9: Causality with Less Modeling]
[Lecture 9b: Instrumental Variables in Action]