Individual skill
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.
Journal-of-Econometrics-Skills/skills/joe-data-analysis/SKILL.md
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# 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