| name | jmcb-robustness |
| description | Use when a Journal of Money, Credit and Banking (JMCB) result may be specification-, sample-, or inference-sensitive and you need to plan checks that each kill a specific threat. Builds a threat-mapped robustness suite; it does not re-run the core identification or write the prose. |
Robustness Strategy (jmcb-robustness)
When to trigger
- The headline (an IRF, an elasticity, a counterfactual welfare number) might flip under nearby choices
- A referee will ask "is this the recursion ordering / lag length / sample window talking?"
- Standard errors look too tight for a bank×time panel or for serially correlated macro data
- The result depends on one regime (a crisis, the ZLB) and you have not shown sub-sample stability
- You have a pile of "robustness" tables but cannot say which threat each one rules out
The JMCB robustness logic
JMCB referees do not reward a wall of additional regressions; they reward checks that are mapped to a named threat to the specific identification. A robustness suite is a list of "the result could be wrong because X — here is the check that rules out X." Given the journal's monetary/banking focus, the recurring threats are: shock contamination, specification dependence (lags, ordering, controls), inference understatement on panels and serially correlated series, and regime/sample instability around crises and policy transitions.
Threat → check map (build yours from this)
| Named threat | Diagnostic / check |
|---|
| Shock is contaminated (information effect, anticipation) | Re-identify with info-robust surprises; orthogonalize to forecast revisions; placebo on pre-announcement windows |
| SVAR result is ordering-/restriction-driven | Vary recursive ordering; alternative sign-restriction sets; report the full identified set |
| IRF is lag-length / horizon dependent | Vary VAR lags; local-projection vs. VAR; alternative horizons |
| Panel SEs understated | Two-way (bank and time) clustering; wild-cluster bootstrap with few clusters; Driscoll–Kraay for cross-sectional dependence |
| Result is one-regime (crisis/ZLB) artifact | Split pre/post-2008, exclude crisis, exclude ZLB; state-dependent specification |
| Demand contamination (micro-banking) | Tighter fixed effects (firm×time); single-bank-firm vs. multi-bank-firm subsample |
| Controls are doing the work | Sequentially add controls (Oster-style movement check); show coefficient stability |
| Outliers / measurement | Alternative winsorizing; drop largest institutions; alternative variable definitions |
How to present it
- Lead with the threats a JMCB referee will actually raise, ordered by how damaging they would be if true.
- For each, show the headline magnitude next to the baseline so the reader sees stability (or honest movement), not just significance survival.
- Put the 3–4 load-bearing checks in the main text; relegate the long tail to the online appendix with a pointer (see
jmcb-internet-appendix).
- Where a check does move the result, say so and interpret it — a transparent boundary is more credible than a uniform table of survivors.
Inference deserves its own pass
For JMCB's two dominant data shapes, the default standard errors are usually wrong in a predictable direction:
- Bank/firm panels: a single dimension of clustering understates uncertainty when shocks are common across units within a period. Cluster on both the cross-sectional unit (bank/firm) and time; with few clusters in either dimension, use the wild-cluster bootstrap (Cameron–Gelbach–Miller). If cross-sectional dependence is plausible, report Driscoll–Kraay as a complement.
- Macro time series / local projections: serially correlated errors require HAR/Newey–West or lag-augmentation; for VARs, report bootstrap or bias-corrected bands rather than asymptotic ones at short samples.
State the clustering/inference choice once, prominently, and show the headline survives a reasonable alternative — referees treat a casual one-way-clustered SE as a red flag.
Crisis and regime stability is not optional for long samples
Many JMCB samples straddle the 2008 crisis, the ZLB/QE era, and post-Basel-III regulation. A result that holds only because one of these episodes dominates the variation is fragile. Show the headline in pre/post sub-samples, excluding the crisis window, and — where the mechanism plausibly changes at the bound — in a state-dependent specification (e.g., interacting the shock with a ZLB or high-uncertainty indicator). If the effect genuinely is regime-specific, that is itself a finding; report it as one rather than letting it masquerade as a general result.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JMCB is monetary/banking — macro time series + bank panels; local projections for the macro lane, DiD/IV for the bank 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 robustness section that adds controls and reports "still significant" without showing the magnitude
- Twenty appendix tables with no statement of which threat each addresses
- Reporting only the checks that survive and quietly dropping the ones that did not
- Leaving panel SEs one-way clustered when shocks are common across banks in a period
- Claiming generality from a single regime without a crisis/ZLB sub-sample
- Treating statistical-significance survival as the bar when the question is magnitude stability
Don't over-test: a focused suite beats an exhaustive one
A robustness section that runs every permutation signals uncertainty, not rigor. Pick the checks that map to the objections a JMCB referee will actually raise (shock cleanliness, demand contamination, inference, regime stability) and present those in the body with magnitudes side by side. Everything else — alternative winsorization thresholds, dozens of control permutations — goes to the online appendix with a one-line summary in text. The goal is to show the headline is stable where it matters, not to bury the reader.
Worked vignette (illustrative)
An SVAR finds a contractionary monetary shock raises credit spreads. A referee suspects the recursive ordering. The threat-mapped response: re-estimate under three alternative orderings and a sign-restricted scheme, plot the IRFs together, and show the peak spread response stays in a 15–22bp band across all of them (illustrative). One check — using revised instead of real-time data — does shift the peak; the authors report it and argue the real-time version is the policy-relevant one. That honesty reads as strength at JMCB.
Output format
【Journal】Journal of Money, Credit and Banking
【Skill】jmcb-robustness
【Top threats】ranked list of what could make the headline wrong
【Threat → check】each check mapped to the threat it rules out
【Inference fix】clustering dims / few-cluster / serial-correlation handling
【Regime stability】crisis / ZLB / transition sub-samples
【Main vs appendix】load-bearing checks in text; tail mapped to online appendix
【Honest movement】any check that shifts the result + interpretation
【Next skill】jmcb-tables-figures
