From rje-skills
Assembles a reproducible replication package for RJE industrial-organization manuscripts and handles the journal's supporting-information rules, which discourage supplementary material and do not host data/code.
How this skill is triggered — by the user, by Claude, or both
Slash command
/rje-skills:rje-replication-and-data-policyThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- Preparing data and code for an RJE submission or revision
Be precise, because RJE's posture differs from data-mandate journals:
So: there is no openICPSR-style deposit step to plan for here (unlike AEA journals or the QJE Dataverse), but reproducibility still matters to referees, and anything you do attach is governed by the discouraging supporting-information rule.
Build a clean package even absent a mandate — IO referees probe replicability of structural estimates:
run_all) regenerating every table, figure, and counterfactual from the analysis data. Structural estimation is slow — cache intermediate objects, document expected runtime, and store converged parameter estimates.ssc/net package versions, requirements.txt (pyblp, linearmodels), or renv.lock; report solver/optimizer settings and random seeds / starting values for non-convex objectives.IO empirics lean on restricted data. For each, document the access path and the construction code sharable when the raw data cannot move.
| Data source | Typical IO use | What to document (sharable even if data are not) |
|---|---|---|
| Nielsen / Kilts (NielsenIQ) | Retail scanner demand | Kilts Center license; cleaning/aggregation code |
| FSRDC / Census microdata | Plant-level entry/exit, production | RDC approval, disclosure review, construction scripts |
| CMS / claims data | Health-insurance, provider markets | Data-use-agreement terms; variable derivations |
| Proprietary firm data | Auction bids, transaction prices | NDA scope; a synthetic stand-in for the demo run |
Suppose your article estimates a dynamic entry model on FSRDC data and demand on Nielsen data, with a slow GMM step:
run_all: one master script runs demand, supply recovery, the dynamic step, and counterfactuals in order, with a flag to load cached results.run_all regenerates every counterfactual, not just estimation tables.【RJE mandate】formal deposit required? NOT confirmed (待核实) — verify on rje.org/Wiley
【Master script】run_all regenerates all exhibits + counterfactuals? [Y/N]
【Environment pinned】versions + seeds + starting values recorded? [Y/N]
【Restricted data】access + construction documented? [Y/N]
【Supporting info】minimal + justified (discouraged by RJE)? [Y/N]
【Next step】rje-submission
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin rje-skillsAssembles a JDE-compliant replication package (data, code, README, pinned environment) for submission or acceptance. Does not run the analysis.
Builds a JIE-compliant replication deposit (code, data, master script, README) for an international-economics manuscript. Does not run the analysis.
Assembles data and code for a JPubE manuscript under Elsevier's Option C research-data framework, covering data-availability statements, repository deposit/citation/linking, restricted administrative data, and a reproducible package.