Identification & Theory Strategy (rof-identification-strategy)
When to trigger
- The empirical core is panel regressions with controls and an undefended causal claim
- A DID uses two-way fixed effects on staggered timing without modern estimators
- An IV's first stage is weak or its exclusion restriction is unargued
- The paper is theoretical and the assumptions, generality, or proof exposition are the weak link
The RoF credibility bar
RoF referees apply top-three-finance-journal standards to the inferential or logical spine. Because RoF publishes both empirical and theoretical finance, "identification" means two different things — pick the branch matching your paper.
Branch E1 — Empirical: causal design for finance
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Natural experiments / shocks: regulatory changes, index reconstitutions, staggered law adoption. Name the identifying variation in one sentence and defend its exogeneity.
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DID / event study: under staggered adoption, move beyond TWFE (Callaway–Sant'Anna, Sun–Abraham, de Chaisemartin–D'Haultfœuille); report a Goodman-Bacon decomposition and clean pre-trends.
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IV: strong first stage (report F); weak-IV-robust inference when needed; defend the exclusion restriction on economic, institutional, and falsification grounds.
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RDD: density/manipulation test, optimal bandwidth plus robustness, covariate smoothness.
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Asset-pricing inference: correct standard errors (Newey–West, two-way clustering, Shanken for Fama–MacBeth); guard against data-snooping in factor/anomaly work; cluster at the assignment level.
Branch T1 — Theoretical: assumptions, results, proof exposition
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Assumptions: state them economically; flag substantive vs. technical; discuss what breaks if each is relaxed.
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Results: lead with the proposition and its economic message, not the algebra; show it is non-obvious and general enough to matter.
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Proof exposition: keep proofs self-contained in an appendix with intuition in the body; proofs count against the 60-page cap.
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Numerical work: report solver tolerances, convergence, and seeds (see
rof-replication-and-data-policy).
Diagnostics placement grid — body vs. internet appendix
| Design |
Must sit in the body |
Goes to the internet appendix |
| Staggered DID |
event-study plot with pre-trends; heterogeneity-robust estimate next to TWFE |
Bacon decomposition detail; alternative comparison groups |
| IV |
first-stage table with effective F; the exclusion argument in prose |
weak-IV-robust CIs; alternative instruments |
| RDD |
density test; the main RD plot |
bandwidth grid; donut; placebo cutoffs |
| Return event study |
abnormal-return model choice; clustering by event date |
alternative factor models; bootstrap inference |
| Fama–MacBeth / sorts |
Shanken or NW errors; microcap screen statement |
alternative breakpoints; subperiods |
RoF's editors want the identification spine self-contained inside the 60-page envelope; the appendix carries the battery, the body carries the logic.
Worked vignette — a staggered short-sale-ban DID
Illustrative numbers. Twelve European exchanges ban short sales on financial stocks on different 2008–2012 dates. TWFE yields −1.9% on a liquidity outcome; Callaway–Sant'Anna with not-yet-treated controls yields −3.4% — TWFE was diluted by already-treated comparisons. The RoF-grade presentation: lead with the event-study figure (flat pre-trends, 95% bands, joint pre-trend test p = 0.41 reported, not just plotted); one table with both estimators; one sentence naming the identifying variation ("ban dates set by national regulators' crisis calendars, not by stock-level liquidity trends"); and the magnitude translated — 3.4% of the average bid–ask spread, roughly the trading-cost jump of moving the median bank stock one liquidity decile.
Referee pushback and the venue-specific repair
- "Ban timing is endogenous to crisis severity" → show timing is uncorrelated with pre-ban outcome trends; add severity-bin interactions; isolate a subset where the trigger was plausibly external.
- "The exclusion restriction is asserted, not argued" → add a falsification outcome the instrument should not move and cite the institutional document that created the variation — RoF referees reward institutional specificity over econometric hand-waving.
- "Your proposition rides on CARA plus normality" → prove the comparative static for a wider preference class or locate numerically where it breaks; the breaking point goes in the body, the proof in the appendix (which still counts toward the 60 pages).
- "Anomalies like this die out of sample" → pre-commit an international split (e.g., Datastream non-US sample) or a post-publication window before the referee demands one.
Execution bridge (StatsPAI / Stata MCP)
Estimate and audit the design, don't only describe it. Full map:
execution-with-mcp. Review of Finance is the EFA flagship — corporate-causal chain for corporate papers, factor-zoo haircut for asset pricing.
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detect_design → recommend → fit with as_handle=true → audit_result.
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Observational causal claims: staggered DiD (
callaway_santanna / sun_abraham +
bacon_decomposition + honest_did_from_result); IV (effective_f_test +
anderson_rubin_ci); RDD (rdrobust + mccrary_test).
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Experiments: randomization-based inference +
romano_wolf for many-outcome control.
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Sensitivity:
oster_delta / sensemakr for observational claims.
Report the magnitude in interpretable units; route the full battery to the appendix. A
run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.
Anti-patterns
- TWFE on staggered treatment with no heterogeneity-bias discussion.
- An anomaly "discovered" via repeated sorts with no multiple-testing or out-of-sample discipline.
- A theory result that is true by assumption, dressed in heavy notation.
- Over-claiming a local empirical estimate as a universal law, or a knife-edge model as general.
Output format
【Branch】empirical (E1) / theory (T1)
【Spine】identifying variation OR key assumption+result
【Diagnostics done / missing】[...]
【Inference / rigor】clustering & SE OR proof completeness
【Over-claim check】never exceeds design/model? [Y/N]
【Next step】rof-data-analysis