From joe-skills
Prepares code and data materials for a Journal of Econometrics submission under Elsevier data-citation norms, focusing on reproducible Monte Carlo and dataset referencing.
How this skill is triggered — by the user, by Claude, or both
Slash command
/joe-skills:joe-replication-and-data-policyThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- You are assembling the code/data materials for a JoE submission or revision
The Journal of Econometrics applies Elsevier's research-data policy: authors are encouraged to deposit research data in a relevant repository, cite it in the article, and use Elsevier data-linking / co-submission routes where useful. JoE does not present a Journal-of-Applied-Econometrics-style mandatory central archive or Econometric-Society-style Data Editor package as a universal submission requirement in the current Guide for Authors. For JoE, replication materials for applied illustrations should be treated as expected best practice rather than a named central-archive mandate.
Because JoE is a methodology journal, the reproducibility center of gravity is the Monte Carlo and the estimator code, not a large administrative-data archive. Make the method runnable.
[dataset])[dataset].run_all master script that regenerates every Monte Carlo table, every theory figure, and the empirical illustration from raw inputs.renv.lock / requirements.txt / recorded ssc versions / Project.toml; fix and report random seeds and replication counts so simulations reproduce exactly.[dataset] reference-list entryUse this as a second-pass capability check. First lock the estimand or theorem, assumptions, asymptotic/simulation evidence, and applied relevance; then test whether the manuscript addresses econometrics reviewers who expect methodological novelty, assumptions, simulation or empirical illustration, and reproducibility.
claim / evidence / blocker / next edit rows so the next pass can patch the manuscript directly.resources/official-source-map.md for volatile rules and name the one unresolved fact that could change the recommendation.【Data citation】[dataset] entries with DOI/version? [Y/N]
【Availability statement】access conditions stated? [Y/N]
【Estimator artifact】documented, runnable, worked example? [Y/N]
【run_all】regenerates all MC tables + figures + illustration? [Y/N]
【Reproducibility】seeds + versions + reps pinned? [Y/N]
【Archive】staged on stable repo (optional but recommended)? [Y/N]
【Next step】joe-review-process
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin joe-skillsGuides authors through JET's data/code policy: deposit/cite data or explain why not, ensure reproducible computation, and disclose generative-AI use.
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.
Builds a data and code replication package for an Economic Journal manuscript to RES/EJ Data Editor standard, including README, data documentation, and Zenodo deposit preparation. Does not run the analysis.