joe-data-analysis
Use when designing the Monte Carlo study and empirical illustration that demonstrate a Journal of Econometrics (JoE) method works in finite samples. Covers size/power simulation design, DGP stress tests, and the role of the applied illustration relative to the theory.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill joe-data-analysis --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.
# Monte Carlo & Empirical Illustration (joe-data-analysis) ## When to trigger - The theorems are settled but the finite-sample evidence is thin or one-off - A simulation reports point estimates but no size/power, or never stresses the assumptions - You are unsure how large or how diverse the Monte Carlo design must be - You have an empirical illustration but it is doing the wrong job (over- or under-claiming) ## What "data analysis" means at a methodology journal At the *Journal of Econometrics* the empirical work serves the **method**, not the other way around. A theorem describes behavior as $n\to\infty$; the **Monte Carlo** shows the asymptotics bite at realistic sample sizes, and the **empirical illustration** shows the method is usable and yields a sensible answer on real economic data. The applied illustration is a demonstration, **not** the paper's primary contribution — purely applied work without a methodological advance is out of scope here. Build both as evidence that the formal claims hold. ## Monte Carlo design ### Report the right quantities - **Estimators:** bias, RMSE, coverage of confidence intervals. - **Tests:** empirical **size at nominal 5%/10%**, then **size-a
- When to trigger
- What "data analysis" means at a methodology journal
- Monte Carlo design
- Report the right quantities
- Stress the assumptions, do not flatter them
- Computational hygiene
- Finite-sample stress grid
- Empirical illustration
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Output format
What does the joe-data-analysis skill do?
Use when designing the Monte Carlo study and empirical illustration that demonstrate a Journal of Econometrics (JoE) method works in finite samples. Covers size/power simulation design, DGP stress tests, and the role of the applied illustration relative to the theory.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill joe-data-analysis --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.