JFQA Identification Strategy (jfqa-identification-strategy)

Use this skill to make the research design defensible for JFQA, an empirical and quantitative finance journal. JFQA referees press hard on whether a correlation is causal (or, in asset pricing, whether a premium is robust and not data-mined).

Empirical finance designs (the common case)

Pick the design that matches the question and defend it:

• Cross-section of returns — portfolio sorts and Fama-MacBeth regressions; Newey-West / clustered SEs; control for standard factors; report economic magnitudes (return per one-SD change), not only t-stats; guard against data snooping (out-of-sample, multiple-testing awareness).
• Corporate finance panels — firm and time fixed effects, two-way clustering; show the variation that identifies the coefficient.
• Policy / regulatory shocks — staggered DID with a modern estimator (Callaway-Sant'Anna, de Chaisemartin-D'Haultfœuille), event-study leads/lags, and parallel-trends evidence; avoid naive TWFE on staggered timing.
• Natural experiments / IV — instrument relevance (first-stage F), exclusion logic backed by an economic story, weak-IV-robust CIs.
• Thresholds / index reconstitution — RDD with manipulation/density tests and bandwidth robustness.
• Announcements — event study with CARs/BHARs, a defensible market model, and attention to calendar clustering.

What referees demand