Interactive notes for econometrics and causal inference
Open-access teaching notes with browser-based simulations for graduate econometrics and applied causal inference. Every page runs simulations live in your browser; no installs needed.
Probability, regression, MLE/GMM, Bayesian estimation, and the statistical foundations of modern ML.
Potential outcomes, identification strategies, modern treatment-effect estimators, and Bayesian + ML approaches to causal questions.
The spatial structure of cities: land rents and location choice, housing supply, agglomeration, local public goods, and gentrification.
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Notes are drafted with AI assistance and reviewed for clarity against primary sources. Found something wrong, unclear, or missing? Leave feedback.