Written resources on causal inference

Below is a list of written resources (books, blog posts, etc.) that are useful for learning about causal inference.

Quasi-experiment resources

• Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton university press.

• Angrist, J. D., & Pischke, J. S. (2014). Mastering’metrics: The path from cause to effect. Princeton University Press.

• Cunningham, S. (2021). Causal inference: The Mixtape. Yale University Press.

• Huntington-Klein, N. (2021). The effect: An introduction to research design and causality. Chapman and Hall/CRC.

• Reichardt, C. S. (2019). Quasi-experimentation: A guide to design and analysis. Guilford Publications.

Bayesian causal inference resources

• The official PyMC examples gallery has a set of examples specifically relating to causal inference.

General causal inference resources

• Awesome Causal Inference, a curated list of resources on causal inference, including books, blogs, and tutorials.