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jbes-data-analysis
Use when building the Monte Carlo evidence and the substantive empirical application for a Journal of Business & Economic Statistics (JBES) methods paper. Designs and audits the simulation study and the real-data analysis; it does not derive the asymptotic theory (see jbes-identification-strategy).
Journal-of-Business-and-Economic-Statistics-Skills/skills/jbes-data-analysis/SKILL.md
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# Monte Carlo & Empirical Application (jbes-data-analysis)
## When to trigger
- The asymptotic theory exists but the simulation study is thin or one-sided
- The empirical application is a toy illustration rather than a substantive use
- Reviewers will ask "does the method actually work in finite samples / on real data?"
- You need to choose DGPs, baselines, and an application that show the method's value
## Why this matters at JBES
JBES is a methods-with-empirics journal: a contribution is incomplete without **finite-sample evidence** and a **substantive empirical application** in microeconomics, macroeconomics, business, or finance. The simulation study is how you demonstrate the asymptotics bite at realistic sample sizes; the application is how you demonstrate **clear empirical relevance**. Both are evaluated by method experts who will reproduce or interrogate them.
## Monte Carlo design