Jimf empirical design
Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的 Claude Code/Codex 期刊技能包,从选题、识别策略到表格规范与审稿回复全流程,助你快速发论文。
npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill jimf-empirical-designAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Use when the cross-country/time-series data construction, sample, frequency, or measurement of a Journal of International Money and Finance (JIMF) manuscript is the bottleneck. Builds the international dataset and measurement; it does not establish causality (jimf-identification) or run robustness (jimf-robustness).
SKILL.md
9.6 KB, as published. Nobody here has run it
Empirical Design (jimf-empirical-design)
When to trigger
- A cross-country panel is unbalanced, mixes incompatible series, or pools regimes that should be separated
- Frequency and alignment are unclear (daily FX vs. monthly flows vs. quarterly macro) and the design glosses the mismatch
- Key variables (exchange rate, capital flows, sovereign spread, pass-through) are measured in a way a referee will dispute
- Country coverage, the advanced-vs-emerging split, or sample period drives the result and is not justified
- Standard data quirks (USD vs. trade-weighted FX, gross vs. net flows, BoP vs. EPFR, nominal vs. real) are not pinned down
The JIMF data-design bar
International-finance referees scrutinize measurement and comparability as hard as identification, because cross-country data are heterogeneous and easy to mis-align. Three recurring fault lines: (1) which series — there are several defensible measures of every JIMF object, and the choice matters; (2) which countries and period — advanced vs. emerging, pre- vs. post-GFC, in-vs-out of a crisis window; (3) what frequency and alignment — mixing frequencies without saying how. Make each explicit and defend it before the result.
| JIMF object | Measurement choices to declare | Common referee objection |
|---|---|---|
| Exchange rate | bilateral USD vs. NEER/REER; nominal vs. real; end-of-period vs. average | "Your result is a dollar effect, not an exchange-rate effect" |
| Capital flows | gross vs. net; BoP (quarterly) vs. EPFR (high-frequency fund flows); by instrument (debt/equity/bank) | "EPFR is fund flows, not balance-of-payments flows" |
| Pass-through | import prices vs. CPI; aggregate vs. invoicing-currency level; horizon of pass-through | "Aggregate ERPT hides the dominant-currency margin" |
| Sovereign risk | CDS vs. EMBI/bond spread vs. rating; local- vs. foreign-currency debt | "LC and FC sovereign risk are different objects" |
| Global financial cycle | VIX vs. a factor (Miranda-Agrippino–Rey) vs. US shadow rate | "VIX is a proxy, not the GFCy" |
| Monetary stance | policy rate vs. shadow rate vs. surprise; domestic vs. foreign | "The ZLB period breaks your policy-rate measure" |
Design moves that read as JIMF-competent
- Declare the country set and the split. State advanced vs. emerging, why each country is in, and report results separately if the mechanism differs — pooling AE and EM without a test invites rejection.
- Anchor the sample period to the institutional history. Bretton-Woods break, euro introduction, GFC, ZLB, taper tantrum, COVID — say which regimes your window spans and whether you split them.
- Resolve the frequency mismatch explicitly. If the shock is daily and the outcome quarterly, state the aggregation; if you use mixed frequency, justify it (MIDAS / local projections at the native frequency).
- Defend the exchange-rate convention. Distinguish a dollar effect from a general exchange-rate effect; report NEER/REER alongside USD when the claim is about the exchange rate per se.
- Document sources to the series level. BIS, IMF IFS/BoP, IMF AREAER (capital-account openness), EPFR, Datastream/Bloomberg, Lane–Milesi-Ferretti external positions, Ilzetzki–Reinhart–Rogoff regime classification — name the exact vintage and any splicing.
Execution bridge (StatsPAI / Stata MCP)
Run the asset-pricing battery, don't just specify it. Full map:
execution-with-mcp. JIMF is international macro-finance; cross-country panels + asset pricing — identification plus factor/Newey-West inference.
- Factor regressions / time-series alphas:
feolswith the right SEs (Newey–West / clustered) — read the alpha and t off the return. - Factor-zoo haircut: after disclosing how many signals were screened, apply
romano_wolf/benjamini_hochbergand report the alpha that survives. - Fama–MacBeth + Shanken EIV are Stata-canonical — run via
mcp__stata-mcp__stata_dowith the vendoredresources/code/(asreg/xtfmb). - Exhibits:
etable; hand formatting to the tables/figures skill.
Report the economic magnitude (bps/month alpha, Sharpe gain); full factor grid → appendix. JF execution walkthrough.
Checklist
- Country set justified; AE/EM split reported or its absence defended
- Sample period mapped to international monetary history; regime breaks handled (split or controlled)
- Each JIMF object measured with a declared, defended choice (USD vs. NEER, gross vs. net, CDS vs. spread)
- Frequency alignment stated; mixed-frequency method named if used
- Data sources named to the series and vintage; splicing/cleaning documented for audit
- A dollar effect is not mislabeled as an exchange-rate effect (and vice versa)
- Sample-construction steps reproducible enough for the online appendix and Mendeley Data deposit
Anti-patterns
- Pooling advanced and emerging economies with no test for whether the mechanism is common
- Using EPFR fund flows and calling them balance-of-payments capital flows (or vice versa) without flagging the difference
- A "global financial cycle" measured only by VIX with no acknowledgment it is a proxy
- An unbalanced panel where entry/exit of countries correlates with the outcome (crisis countries dropping out)
- Spanning the GFC and ZLB with a single policy-rate measure and no regime control
- Hiding the exchange-rate convention so a dollar-specific result reads as a general exchange-rate result
Worked vignette (illustrative)
A draft regresses quarterly EM "capital flows" on a daily US surprise and finds a strong effect, but the flows are EPFR weekly fund flows aggregated to quarters and the panel drops three countries during their crises. The JIMF fix: state that EPFR captures benchmarked-fund flows (a leading indicator), not BoP flows, and either align the analysis at the native weekly frequency via local projections or report both; keep the crisis countries in with a balanced-panel robustness; and report whether the effect is a dollar phenomenon (USD bilateral) or survives in NEER terms.
Referee pushback mapped to the design fix
- "That's a dollar effect, not an exchange-rate effect." → Report NEER/REER alongside the USD bilateral; show whether the result is dollar-specific or holds for the effective rate.
- "EPFR is not balance-of-payments capital flows." → State what EPFR measures (benchmarked-fund flows, a high-frequency leading indicator) and either align at its native frequency or triangulate with BoP data.
- "Your panel is unbalanced in a way that correlates with the outcome." → Show a balanced-panel robustness; report whether crisis-driven entry/exit moves the estimate.
- "You pooled advanced and emerging economies." → Split AE/EM and test whether the mechanism is common before pooling.
- "The ZLB breaks your policy-rate measure." → Use a shadow rate or a monetary surprise over the affected window; show the result is not an artifact of the policy-rate floor.
A note on sources international-finance referees trust
Name the canonical datasets and their roles so the design reads as field-literate: IMF IFS/BoP for macro and flows; BIS for cross-border banking and FX statistics; IMF AREAER and the Chinn–Ito index for capital-account openness; the Ilzetzki–Reinhart–Rogoff classification for de facto exchange-rate regimes; Lane–Milesi-Ferretti for external positions; EPFR for high-frequency fund flows; Datastream/Bloomberg for prices, CDS, and yields. Using the wrong dataset for an object (e.g. a de jure regime classification when the question is de facto behavior) is a credibility tell referees catch quickly.
Pre-analysis design questions to settle first
Before estimating, lock five decisions and write the one-line justification for each — they are the questions a referee asks before reading Table 1:
- Outcome and treatment frequency — at what frequency is each measured, and how are they aligned (aggregation, MIDAS, native-frequency local projections)?
- Country set and entry/exit rule — which countries, why, and what happens to crisis-driven gaps in the panel.
- Regime/period partition — which exchange-rate or policy regimes the window spans, and whether you split or control for the breaks.
- The exchange-rate convention — USD bilateral, NEER, or REER, nominal or real, and whether the claim is about the dollar or the effective rate.
- The flow/risk object — gross vs. net, BoP vs. fund flows, CDS vs. spread, and which the mechanism actually predicts.
Settling these up front prevents the most common revision loop, where a measurement choice the authors never justified turns out to drive the headline result.
Output format
【Journal】Journal of International Money and Finance
【Skill】jimf-empirical-design
【Country set / split】AE / EM / both → justified? [Y/N]
【Sample period / regimes】window + breaks handled
【Key measures declared】FX convention / flows type / risk measure / GFCy proxy
【Frequency】native / aggregated / mixed-frequency method
【Data sources】named to series + vintage; splicing documented? [Y/N]
【Next skill】jimf-robustness