Agent skill · Data & Analytics

aejmic-identification

Use when the question is what makes the result tight or what the data identify for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering both (a) structural/empirical-IO and experimental identification and (b) for pure theory, which assumptions drive the result and how robust the mechanism is. Stress-tests credibility; it does not build the model (see aejmic-theory-model).

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-identification --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 7 KB
Bundled scripts: none
Path: AEJ-Microeconomics-Skills/skills/aejmic-identification/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Identification & What Makes the Result Tight (aejmic-identification) AEJ: Micro is theory-first, so "identification" here is **two things**. For pure theory it means: **which assumptions are doing the work**, and how tight/robust the mechanism is. For structural and experimental work it means the standard **data-to-object mapping**. Pick the branch. ## When to trigger - (Theory) A referee asks whether the result is a knife-edge artifact of one assumption - (Theory) You cannot say cleanly which primitive drives the comparative static - (Structural) Parameters are estimated but it is unclear *what in the data* identifies them - (Experimental) The estimand or the assumptions behind the treatment effect are not pinned down ## Branch A: Pure theory — what makes the result tight The AEJ: Micro bar is that the reader sees **exactly which assumption is load-bearing** and how far the mechanism extends. - **Decompose the assumptions.** For each substantive assumption, ask: is the result *false* without it, *weaker* without it, or *unchanged* (then it was WLOG — say so)? The result is "tight" when you can name the assumption that breaks it. - **Comparative statics as identification.** Show

What's inside
Steps it walks through
  1. When to trigger
  2. Branch A: Pure theory — what makes the result tight
  3. Branch B: Structural / empirical IO
  4. Branch C: Experimental (theory-grounded)
  5. Execution bridge (StatsPAI / Stata MCP)
  6. Checklist
  7. Anti-patterns
  8. Worked vignette (illustrative)
  9. Output format
More from Awesome-Journal-Skills
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About this skill
What does the aejmic-identification skill do?

Use when the question is what makes the result tight or what the data identify for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering both (a) structural/empirical-IO and experimental identification and (b) for pure theory, which assumptions drive the result and how robust the mechanism is. Stress-tests credibility; it does not build the model (see aejmic-theory-model).

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-identification --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.

Keep going