mostly-harmless-guide
Replication code and guide for Mostly Harmless Econometrics methods
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill mostly-harmless-guide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Mostly Harmless Econometrics Guide A skill providing replication code, explanations, and practical guidance for the econometric methods presented in Angrist and Pischke's "Mostly Harmless Econometrics" (MHE). Based on the mostly-harmless-replication repository (642 stars), this skill helps researchers understand and correctly apply core causal inference techniques. ## Overview "Mostly Harmless Econometrics" is one of the most influential applied econometrics textbooks, providing accessible explanations of the methods that dominate modern empirical research in economics and increasingly in other social sciences. This skill translates the book's core methods into practical guidance that the agent can use to help researchers design studies, select appropriate estimators, and interpret results correctly. The skill covers regression, instrumental variables, difference-in-differences, regression discontinuity, and related methods, with emphasis on the practical decisions researchers face when applying these techniques to real data. ## Regression Fundamentals **Ordinary Least Squares (OLS)** - OLS provides the best linear approximation to the conditional expectation function - The regre
- Overview
- Regression Fundamentals
- Instrumental Variables
- Difference-in-Differences
- Regression Discontinuity
- Integration with Research-Claw
- Best Practices
What does the mostly-harmless-guide skill do?
Replication code and guide for Mostly Harmless Econometrics methods
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill mostly-harmless-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.