Robustness Strategy (ecopol-robustness)
SkillSecurityUse when an Economic Policy (EP) manuscript's results may be specification-, sample-, or inference-fragile, especially ahead of the two-discussant panel. Organizes robustness by the threat a discussant will raise; it does not invent evidence or citations.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Robustness Strategy (ecopol-robustness) skill
What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in Economic-Policy-Skills/skills/ecopol-robustness/SKILL.md and read by ahel’s review.
When to trigger
- The headline policy magnitude moves under plausible alternative specifications
- A discussant could attribute the result to one sample, period, or country
- Inference rests on few clusters / few treated units (common in policy evaluations)
- The result is statistically significant but the magnitude — the part a policymaker uses — is imprecise
- You are pre-empting the academic discussant's "have you tried…" before the conference
Robustness is discussant-proofing, not a checklist dump
At EP, robustness has a specific purpose: the paper will be debated live by two invited discussants who act as the referees, and the academic one will arrive with a list of fragility tests. So organize robustness by the threat each test neutralizes, not as a mechanical appendix of "alternative specifications." A reader (and the policy discussant) should see, for each test, which way of being wrong it rules out. Because EP papers carry a recommendation, the central object to defend is the magnitude and its confidence interval, not just the sign.
The threat-to-test map (build the robustness section from this)
| Threat a discussant will raise | The test that answers it |
|---|---|
| "It's driven by one period/sample" | leave-one-out by year/region; pre/post-crisis split |
| "Functional form is doing the work" | alternative specifications; semi/non-parametric check |
| "Parallel trends / pre-trends fail" | event-study leads; honest-DID / pre-trends sensitivity bounds |
| "Confounders you didn't control for" | coefficient-stability / Oster δ bounds; placebo on unaffected groups |
| "Inference is too optimistic with few clusters" | wild-cluster bootstrap; randomization inference |
| "Measurement error in the policy variable" | alternative coding; instrument or bound the error |
| "It won't generalize beyond this case" | replicate on a second jurisdiction/episode if data allow |
Craft moves
- Put a robustness summary in the main text, not buried 40 pages deep: a compact figure or sentence showing the headline number is stable across the threats that matter. The policy discussant will not read the appendix.
- Distinguish robustness from heterogeneity. Stable-everywhere = robust; differs-by-group = a finding to report, not a failure to hide.
- Report the range, not just a star. "The effect lies between X and Y across all specifications" is the EP-useful statement.
- Pre-register the discussant's likely objections (use
ecopol-referee-strategy) and answer the top three in the main text proactively — you cannot reply live as easily as in a referee letter, so anticipate. - Honesty about fragility. If one test moves the number, say what it implies for the policy conclusion rather than hiding it — discussants will find it.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. Economic Policy is policy-facing applied economics; foreground a credible design and a policy-relevant magnitude.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley. - Re-fit off one handle:
audit_result(result_id)lists missing checks + the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Decisive checks in the body, exhaustive battery in the appendix. JF execution walkthrough.
Checklist
- Robustness section organized by threat, each test labeled with the threat it neutralizes
- A main-text robustness summary (figure or sentence) — not appendix-only
- Headline magnitude + CI shown to be stable (or its instability honestly bounded)
- Few-cluster / few-treated inference addressed (wild bootstrap / randomization inference)
- Pre-trends / parallel-trends sensitivity reported where the design needs it
- Coefficient-stability or placebo evidence against unobserved confounders
- Heterogeneity reported as a finding, not disguised as robustness
- Top three likely discussant objections answered proactively in the main text
Anti-patterns
- A 20-table appendix of "alternative specifications" with no map to the threats they address
- Defending only significance while the policy-relevant magnitude swings across specifications
- Standard clustered SEs with five treated jurisdictions and no few-cluster correction
- Burying every robustness result in the appendix where the policy discussant never sees it
- Quietly dropping a specification that breaks the result instead of reporting and interpreting it
Output format
【Journal】Economic Policy (EP)
【Skill】ecopol-robustness
【Headline magnitude】X (CI: [.,.]) — stable across threats? Y/N
【Threats neutralized】[sample / functional form / pre-trends / confounders / inference / measurement / external]
【Main-text summary】figure/sentence present? Y/N
【Few-cluster inference】method used
【Honest fragility note】what moves the number and the policy implication
【Next skill】ecopol-tables-figures
Signals
- GitHub stars
- 1k
- Forks
- 155
- Last commit
- Sep 2026
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ecopol-robustness- Source
- github.com/brycewang-stanford/awesome-journal-skills
github.com/brycewang-stanford/awesome-journal-skills
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