Causal Inference Blog Series

By Laurence Wong

This blog series offers a practical introduction to causal inference using the Causalinference Python package. It is structured as a step-by-step walkthrough of a typical causal study, combining core econometric ideas with concrete code examples.

1. Introduction
2. Notation
3. Setting
4. Initialization
5. Example
6. Balance
7. Least Squares
8. Matching
9. Propensity Score
10. Trimming
11. Stratification
12. Blocking
13. Weighting
14. Conclusion

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🛠️ GitHub Repository · 📦 PyPI Package · 📖 Vignette (PDF)