Causal Inference -- 21/23 -- Staggered Adoption Designs II

This series of online lectures covers the most important causal research designs in economics and other social sciences. This is the first of five videos on Difference-in-Differences (DiD). The video continues with the discussion of staggered adoption designs.
The course is based on two textbooks:
- Mostly Harmless Econometrics by Joshua Angrist and Steve Pischke (2009): press.princeton.edu/books/pap...
- Causal Inference -- the Mixtape by Scott Cunningham (2020): mixtape.scunning.com/
The slides for the course can be downloaded here: 8650ac82-9ca9-4f0f-936f-a74eb...
Course outline:
1 Basics of causal inference (2 videos)
2 Instrumental variables (5 videos)
3 Marginal treatment effects (4 videos)
4 Regression discontinuity and kink designs (4 videos)
5 Difference-in-differences (5 videos)
6 Synthetic control (2 videos)
Get in touch:
- follow me on twitter: / ben_elsner
- website: www.benjaminelsner.com
- profile on linkedin: / benjamin-elsner-b71b98bb

[@michaelion8620]

These videos have been a wonderful resource in helping with my read of Causal Inference: The Mixtape. Thanks for posting these!

[@sandymaulana8358]

Terrific. This is great sources and you are a wonderful instructor!

[@midori8er]

Great video! Thanks!

[@jasonchen8794]

Intuitively, shouldn't we take into account the fact that different groups may influence each other during the time period? Common trend assumption may not hold while later-adoption groups and never-adoption groups under pressure of early-adoption groups?

[@ben_elsner]

Good point. An important assumption is called SUTVA, which basically states that there are no spillovers. Spillovers can lead to biased estimates; problem is that they are hard to deal with.