| name | ecj-robustness |
| description | Use when the main result of a The Economic Journal (EJ) manuscript rests on a single specification and you need to pre-empt the alternative-explanation and fragility objections a demanding referee will raise. Builds the robustness battery and the falsification logic; it does not establish the primary identification (see ecj-identification). |
Robustness & Alternative Explanations (ecj-robustness)
When to trigger
- The headline result is one regression with one set of choices
- You have not ruled out the obvious competing economic explanations
- A structural result has not been shown to survive perturbing key assumptions
- You suspect a referee will say "this is fragile" or "this is mechanism A, not your mechanism B"
The EJ logic of robustness
At EJ, robustness is not a ritual table of "still significant." It is an argument that the economic interpretation survives, and that rival mechanisms are ruled out — and because the interpretation is what makes the result broadly interesting, fragility there is fatal. A demanding general-interest referee thinks adversarially: which alternative economic story produces the same coefficient, and how do you exclude it? Over-reliance on a single specification is an explicit anti-pattern. And because acceptance triggers the EJ Data Editor rerunning your code against the Zenodo deposit (RES policy, DCAS-endorsed; see ecj-replication-package), every robustness number must come from code that actually executes and reproduces — fragility you papered over will surface in verification. Distinguish three jobs:
- Specification robustness — the number is not an artifact of arbitrary choices.
- Mechanism discrimination — your channel, not a competing one, drives it.
- External / structural validity — the result generalizes (it must, for EJ's broad-interest bar) / the model's conclusions are not knife-edge.
For a short paper (AER:Insights-style), keep the headline robustness in the tight exhibit budget and push the rest to an online appendix — but the leading rival mechanism must still be addressed.
What to run
Specification robustness
- Vary controls (parsimonious → saturated); show coefficient stability and use Oster (2019) δ / bounds for selection on unobservables.
- Alternative functional forms, sample windows, and exclusion of influential subsamples.
- Alternative standard-error structures (clustering level, wild bootstrap with few clusters).
- Inference robustness: randomization inference or permutation tests where design allows.
Mechanism discrimination (the broad-interest part)
- Name the 2–3 alternative economic mechanisms that could generate the same reduced-form sign.
- For each, design a test that the alternatives fail and your mechanism passes (heterogeneity only your channel predicts, an auxiliary outcome, a dose-response the rival cannot explain).
- Triangulate: a second data source, a second identification strategy, or a structural-vs-reduced-form cross-check.
External validity / structural papers
- Argue (or bound) how far the estimate generalizes — central to EJ's broad-relevance claim.
- Sensitivity of estimates and counterfactuals to identifying assumptions and to fixed/calibrated parameters.
- Untargeted-moment fit; over-identification evidence; alternative model specifications that nest or rival the baseline.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. The Economic Journal is general-interest economics; the DiD/IV/RDD chain serves its broad applied lane.
- Many outcomes / specifications:
romano_wolf (step-down FWER) or benjamini_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 exact
suggest_function for each.
- Exhibits:
etable / did_summary_to_latex from the handle — no retyped numbers.
Decisive checks in the body, exhaustive battery in the appendix.
JF execution walkthrough.
Checklist
Anti-patterns
- A wall of "still significant" tables that never address why the effect is your mechanism
- Treating robustness as cosmetic while the headline rival explanation goes untested
- Reporting only specifications that work; hiding the fragile ones (a referee will ask, and the EJ Data Editor reruns the code)
- Selection-on-unobservables waved away with "we control for X" and no bound
- Asserting the result generalizes without any external-validity evidence
- Burying so many checks in the main text that the economic story is lost (use the online appendix)
Output format
【Headline result】coefficient + interpretation
【Spec robustness】[controls, windows, SEs, Oster δ, ...]
【Rival mechanisms】1... 2... — test that discriminates each
【Triangulation】second source / design / structural cross-check
【External validity】how far it generalizes (or bound)
【Residual fragility】honest statement of what is not bulletproof
【Next】ecj-tables-figures
