econometrics-check
Causal inference design audit for the sewage-house-prices project. Runs a 4-phase review (claim identification, design validity, inference, polish) covering hedonic pricing, repeat sales, long difference, DiD/event studies, upstream/downstream, and dry spill strategies. This skill should be used when asked to "check the econometrics", "audit the identification", "review the strategy", or when verifying that code matches the stated design.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill econometrics-check --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 Check Run a 4-phase causal inference audit on the target file(s) for the sewage-house-prices project. **Input:** `$ARGUMENTS` — a `.tex` file, `.R` script, directory path, or `all`. --- ## Project-Specific Context ### Identification Strategies in This Paper 1. **Hedonic regressions** — Cross-sectional: `log(price)` on spill count/hours (continuous + bins), LSOA FE, heteroskedasticit
What does the econometrics-check skill do?
Causal inference design audit for the sewage-house-prices project. Runs a 4-phase review (claim identification, design validity, inference, polish) covering hedonic pricing, repeat sales, long difference, DiD/event studies, upstream/downstream, and dry spill strategies. This skill should be used when asked to "check the econometrics", "audit the identification", "review the strategy", or when verifying that code matches the stated design.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill econometrics-check --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.