This video is the second part of our mini course on application of Causal Inference in data science. We are going to discuss what kind of methods you can use to do Causal Inference with just a few treated units. Two methods are introduced: difference-in-differences and synthetic control.

🔗 Regression and Matching    • Regression and Matching | Causal Infe...  

📃Yuan's blog post on causal inference https://www.yuan-meng.com/posts/causa...

📚 Resources recommended by Yuan
- Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425.
- Jones, N., & Barrows, S. (2019, July 24). Uber’s synthetic control. PyData Amsterdam 2019.    • Nick Jones, Sam Barrows: Uber's Synth...  
- Python/R/Stata code from The Effect: An Introduction to Research Design and Causality: https://github.com/NickCH-K/causaldata
- The “synth” package for synthetic control: https://rpubs.com/danilofreire/synth
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Contents of this video:
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00:00 How to measure COVID's Impact on the Economy
08:13 Difference-in-Differences
14:47 Synthetic Control
24:17 Summary