Mastering Causal Metrics
Welcome to Mastering Causal Metrics!
An AI-powered study guide to Mastering Causal Metrics. Learn the foundations of causal inference with interactive Python notebooks and AI tools, based on the foundational textbook Mastering ‘Metrics: The Path from Cause to Effect by Angrist & Pischke.
This platform features:
- Foundational Methods – Based on Mastering ‘Metrics by Angrist & Pischke. Learn causal inference from randomized trials to differences-in-differences.
- Python Notebooks – Zero-installation Google Colab notebooks. Real datasets, working code, and complete implementations of every method.
- AI-Powered Learning – Multiple AI tutors with distinct pedagogical styles.
Interactive Google Colab Notebooks
Click any badge below to open and run immediately in your browser:
Part I: The Framework
| Chapter | Title | Topics | Colab Notebook |
|---|---|---|---|
| 1 | Randomized Trials | Selection Bias, Potential Outcomes, RAND HIE |  |
Part II: The Five Tools
| Chapter | Title | Topics | Colab Notebook |
|---|---|---|---|
| 2 | Regression | OLS, Omitted Variable Bias, Bad Controls | |
| 3 | Instrumental Variables | LATE, Compliers, Minneapolis DV Experiment | |
| 4 | Regression Discontinuity | Sharp RD, Bandwidth, MLDA and Mortality | |
| 5 | Differences-in-Differences | Parallel Trends, Two-Way FE, Great Depression Banking | |
Part III: Synthesis
| Chapter | Title | Topics | Colab Notebook |
|---|---|---|---|
| 6 | The Wages of Schooling | Twins, Quarter of Birth, Sheepskin Effects | |
How to Use the Notebooks
- Click any “Open in Colab” badge above
- Sign in with your Google account (free)
- Click “Run All” in the Runtime menu (or run cells individually)
- Explore and modify – change parameters, try different models, experiment with the data
- Save your work – File > Save a copy in Drive to keep your modifications
No installation, no downloads, no setup required!
Authors and Credits
Carlos Mendez – Python implementation and educational notebook development
Joshua D. Angrist & Jorn-Steffen Pischke – Original textbook, Mastering ‘Metrics
Carlos Mendez
Associate Professor of Development Economics
My research interests focus on the integration of development economics, spatial data science, and econometrics to better understand and inform the process of sustainable development across regions.