aejmac-identification
Use when the empirical identification of a macro shock or dynamic causal effect is the bottleneck for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript — SVAR, local projections, narrative, high-frequency/proxy-VAR, or micro-data macro designs. Stress-tests the identification to the AEJ: Macro broad-interest quantitative bar; for model-parameter identification see aejmac-theory-model.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmac-identification --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 Identification (aejmac-identification) ## When to trigger - The macro effect rests on a recursive (Cholesky) SVAR with no defense of the ordering - A monetary/fiscal "shock" is plausibly anticipated or endogenous to the cycle - Local projections are run but lag length, controls, and inference are ad hoc - A narrative or high-frequency instrument is used but its exogeneity/relevance is unargued - You are unsure the design clears AEJ: Macro's identified-empirical bar ## The AEJ: Macro identification bar AEJ: Macro publishes identified-empirical macro, so the **mapping from data to the dynamic causal object** (an impulse response, a multiplier, a pass-through) must be explicit and defended. The aggregate, time-series setting makes identification harder than in micro: few effective observations, anticipation, simultaneity, and structural breaks. State the **shock you claim to identify**, the **assumption that delivers it**, and the **horizon and object** you report. Report **standard errors / confidence bands** (the AEA house style; significance asterisks are conventional in AEA tables but the band/SE must carry the inference, not the stars). ## Branch paths ### Branch A: S
- When to trigger
- The AEJ: Macro identification bar
- Branch paths
- Branch A: Structural VAR (SVAR)
- Branch B: Local projections (LP)
- Branch C: Narrative & high-frequency identification
- Branch D: Micro-data macro / cross-sectional identification
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Worked vignette: identifying a monetary shock (illustrative)
- Output format
What does the aejmac-identification skill do?
Use when the empirical identification of a macro shock or dynamic causal effect is the bottleneck for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript — SVAR, local projections, narrative, high-frequency/proxy-VAR, or micro-data macro designs. Stress-tests the identification to the AEJ: Macro broad-interest quantitative bar; for model-parameter identification see aejmac-theory-model.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmac-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.