econometrics-skills
12 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill econometrics --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.
# Econometrics — 12 Skills Select the skill matching the user's need, then `read` its SKILL.md. | Skill | Description | |-------|-------------| | [causal-inference-guide](./causal-inference-guide/SKILL.md) | Causal inference methods including DiD, IV, RDD, and synthetic control | | [econml-causal-guide](./econml-causal-guide/SKILL.md) | Apply EconML for causal inference combining machine learning
What does the econometrics-skills skill do?
12 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill econometrics --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.