jfe-empirical-design
Use when settling the measurement and estimation choices of a Journal of Financial Economics (JFE) manuscript — factor construction, portfolio sorts, Fama-MacBeth/GMM, standard-error clustering, and multiple-testing discipline. Covers the design/estimator layer; for causal identification of corporate-finance effects use jfe-identification.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfe-empirical-design --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.
# Empirical Design & Inference (jfe-empirical-design) ## When to trigger - You sort on a characteristic but have not justified the variable, the breakpoints, or weighting - You are choosing between Fama–MacBeth, panel regression, and GMM and unsure how to report - Your standard errors are unclustered, or clustered on one dimension when two are needed - You have an asset-pricing predictor but no out-of-sample or multiple-testing treatment - Variable definitions are ad hoc and would not replicate ## The JFE design bar JFE is known for nuts-and-bolts methodological rigor. Referees scrutinize measurement, estimator choice, standard errors, and inference discipline line by line. The goal is a design that a skeptical expert cannot dismantle on technical grounds. This is the journal that published **Fama & French (1993), "Common risk factors in the returns on stocks and bonds"** (the three-factor model), **Fama & French (2015), "A five-factor asset pricing model,"** and **Banz (1981), the size effect** — so an asset-pricing referee benchmarks your construction against that lineage directly. The best capital-markets paper each year wins JFE's **Fama-DFA Prize**; write to that standard. Cod
- When to trigger
- The JFE design bar
- Asset pricing
- Factor / portfolio construction
- Cross-sectional inference
- Inference discipline
- Corporate finance
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the jfe-empirical-design skill do?
Use when settling the measurement and estimation choices of a Journal of Financial Economics (JFE) manuscript — factor construction, portfolio sorts, Fama-MacBeth/GMM, standard-error clustering, and multiple-testing discipline. Covers the design/estimator layer; for causal identification of corporate-finance effects use jfe-identification.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfe-empirical-design --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/Awesome-Journal-Skills, a repository with 909 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.