Further reading
Econometrics and causal inference is a very large field, which can’t possibly be completely covered in a single chapter. Here are some resources for you to learn more:
- Causal Inference: The Mixtape by Scott Cunningham, Yale University Press
- The Book of Why by Judea Pearl and Dana Mackenzie, Basic Books
- Regressions and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari, Cambridge University Press
- Statistical Rethinking by Richard McElreath, Chapman and Hall
- Causal Inference and Discovery in Python by Aleksander Molak, Packt Publishing
- Causal analysis with PyMC: Answering “What If?” with the new do operator, https://www.pymc-labs.com/blog-posts/causal-analysis-with-pymc-answering-what-if-with-the-new-do-operator/, by Benjamin Vincent and Thomas Wiecki
