--- 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 1. **Lead with the threats a JMCB referee will actually raise**, ordered by how damaging they would be if true. 2. For each, show the headline magnitude **next to** the baseline so the reader sees stability (or honest movement), not just significance survival. 3. 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`). 4. 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`](../../../shared-resources/empirical-methods/execution-with-mcp.md). 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](../../../Journal-of-Finance-Skills/resources/worked-examples/02-execution-walkthrough.md). ## Checklist - [ ] Each robustness check is tied to a named threat to *this* identification - [ ] Inference re-examined: clustering dimensions correct; few-cluster and serial-correlation handled - [ ] Specification dependence shown (ordering/lags/horizon/controls) with magnitudes side by side - [ ] Sub-sample / regime stability shown (crisis, ZLB, policy transition) if the period spans one - [ ] Micro-banking: demand-contamination check via tighter fixed effects or single-vs-multi-bank firms - [ ] Load-bearing checks in main text; long tail in the online appendix with a map - [ ] Any check that moves the result is reported and interpreted, not hidden ## 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 ```text 【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 ```