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.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfqa-identification-strategy --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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. - *
- Empirical finance designs (the common case)
- What referees demand
- Theoretical submissions
- Threat-to-remedy matrix for the JFQA referee report
- Worked vignette: staggered adoption done the JFQA way (illustrative)
- The anomaly-credibility bar in asset pricing
- Execution bridge (StatsPAI / Stata MCP)
- Output format
What does the jfqa-identification-strategy skill do?
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.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfqa-identification-strategy --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.