Methods Lab

Interactive tools for econometrics, causal inference, and applied microeconomics.

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These modules combine my research experience, teaching materials, and AI-assisted drafting—each curated and refined for clarity. Every simulation runs in your browser; no installs needed.

Foundations of Statistical Inference

Simulation-based modules for statistics, econometrics, and causal inference.

Distributions Sampling CLT LLN p-values & CIs Bootstrap Bag of Little Bootstraps Power & MDE Monte Carlo Regression & CEF FWL Omitted Variable Bias MLE Logit & Probit Clustered SEs Delta Method Bias-Variance Model Selection Bayesian Updating Correlation & Causation

Applied Causal Inference

From potential outcomes to modern treatment effect estimators — see selection bias, parallel trends, and reweighting in action.

Potential Outcomes Identification vs Estimation Selection on Observables Difference-in-Differences IV RDD Synthetic Control Sample Selection & Heckman Regression Adjustment IPW Matching Entropy Balancing Doubly Robust Fixed vs Random Effects

Introduction to Bayesian Thinking

Priors, posteriors, shrinkage, and the Bayesian-frequentist divide — built from first principles with no measure theory.

Bayes' Theorem Priors & Posteriors Shrinkage Bayesian vs Frequentist MCMC Hierarchical Models

Interactive Teaching Modules → Health Economics · Urban Economics · more coming