This repository hosts a comprehensive book on causal inference, covering impact estimation and sensitivity analysis techniques. Written as a light-hearted yet rigorous guide, it uses Python and Jupyter notebooks to demonstrate concepts from econometrics and data science. The material spans multiple translations and covers foundational causal inference methods including propensity scores, instrumental variables, and difference-in-differences.