joe-replication-and-data-policy

Development

Use to prepare code and data materials for a Journal of Econometrics (JoE) submission under Elsevier's data-citation and availability norms, including reproducible Monte Carlo and the [dataset] reference tag. Reflects that JoE has no mandatory central replication archive — replication is encouraged, not universally mandated.

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Source SKILL.md: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/Journal-of-Econometrics-Skills/skills/joe-replication-and-data-policy/SKILL.md

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Replication & Data Policy (joe-replication-and-data-policy)

When to trigger

You are assembling the code/data materials for a JoE submission or revision
You need to know whether a mandatory JoE-specific central replication archive is required
You are citing a dataset and need the correct Elsevier format
Your Monte Carlo or empirical illustration must be made reproducible for referees

What JoE actually requires (and does not)

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.

Data citation (Elsevier `[dataset]`)

Cite relevant/underlying datasets in the text and in the reference list, tagged [dataset].
Elements: author(s), dataset title, repository, version, year, persistent identifier (DOI).
Include a data availability statement describing access conditions for any real data used in the illustration.

Reproducible methodology package (best practice)

Estimator as a usable artifact: ship the new estimator/test as a documented function or command (R/Stata/Python/MATLAB/Julia) with a minimal worked example so referees can run it.
run_all master script that regenerates every Monte Carlo table, every theory figure, and the empirical illustration from raw inputs.
Pin versions and seeds: renv.lock / requirements.txt / recorded ssc versions / Project.toml; fix and report random seeds and replication counts so simulations reproduce exactly.
Archive on a stable repository (e.g., Zenodo, openICPSR) even though JoE does not name a central archive — it pre-empts referee replication requests and supports the optional Data in Brief / MethodsX co-submission route via Editorial Manager.

Anti-patterns

Assuming a mandatory, Data-Editor-vetted package like the Econometric Society journals — JoE's current Guide does not name one as a universal requirement
Citing a dataset only in prose, without the [dataset] reference-list entry
Unreproducible Monte Carlo (unreported seeds, package versions, or replication counts)
Shipping results but not the estimator, so referees cannot actually run the method

Reproducibility pass for Journal of Econometrics

Use 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.

Primary move: Name data, code, environment, disclosure limits, and archive/deposit route; unresolved proprietary or ethics barriers must be explicit.
Decision ledger: return claim / evidence / blocker / next edit rows so the next pass can patch the manuscript directly.
Neighbor test: compare against Econometric Theory for proof-first work, JBES for applied statistical methods, Quantitative Economics for economics-theory methods; if the neighboring outlet has the stronger audience claim, recommend re-routing before polishing.
Verification floor: before submission-ready advice, re-open resources/official-source-map.md for volatile rules and name the one unresolved fact that could change the recommendation.

Output format

【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