Individual skill
jfqa-identification-strategy
Use when building a credible identification / research design for a Journal of Financial and Quantitative Analysis (JFQA) empirical finance paper — portfolio sorts and Fama-MacBeth, panel fixed effects, staggered DID on regulatory shocks, IV / natural experiments, RDD at thresholds, and event studies — with the inference finance referees demand. For theoretical submissions, pivot to assumptions, results, and proof exposition.
Journal-of-Financial-and-Quantitative-Analysis-Skills/skills/jfqa-identification-strategy/SKILL.md
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# 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.