Learning Econometrics with PyFixest
A few classes and textbooks have adopted PyFixest for teaching. And for core textbooks in causal inference that have not (yet =) ) , we have (or are planning to) write PyFixest translations (there are also multiple current “good first issues” for this if you’d like to help us).
Textbooks
- Data Analysis for Business, Economics, and Policy (“Gabor’s Data Analysis”). Data and code and Jupyter Notebooks on github
- Coding for Economists: Regression
- Tidy Finance comes with a chapter on fixed effects and clustered standard errors and Differene-in-Differences estimation that uses pyfixest
- The Effect (first edition): our PyFixest translation
- The Panel Data Chapter in the Mixtape. You can find a PyFixest translation here
Textbooks / textbook chapters that we still want to cover:
- The Difference-in-Differences chapter in the Mixtape (github issue here)
- All of the Python translation of Ding’s textbook on causal inference (github issue here)
- The “Brave and True” chapters on Dummy Regression, Instrumental Variables, Difference-in-Differences and Panel Data and Fixed Effects.
Classes
If you are teaching with pyfixest, we’d love to hear from you!
- Econometrics II (taught by Vladislav Morozov at UBonn): Great intro to fixed effects estimation theory. Slides on fixed effects here, full class notes here, github repository
- Empirical Economics (taught at University of Utrecht 2025-2026) - MSc class in empirical economics.
- ECON 526 - MA-level course in quantitative economics, data science, and causal inference in economics, taught at the University of Brisith Columbia. Class notes here
Blog Posts, Notebooks, Videos
If you’ve written a blog post that illustrates how to use pyfixest, please let us know, we’d love to link to it.
- PyData Berlin Presentation (2024) on PyFixest: link