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Restat replication package

Skill brycewang-stanford/Awesome-Journal-Skills/Review-of-Economics-and-Statistics-Skills/skills/restat-replication-package

Use when assembling the data-and-code replication package for a The Review of Economics and Statistics (REStat) manuscript under the journal's Data and Code Availability Policy — the deposit to the REStat Harvard Dataverse with a README that permits replication. Builds the package; it does not run the primary analysis.From its SKILL.md

Install
npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-replication-package

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

4.8 KB, ~1.0k tokens by cl100k_base, as published. Nobody here has run it

Replication Package & Data/Code Policy (restat-replication-package)

When to trigger

  • The paper is approaching acceptance and a data/code deposit will be required
  • You use proprietary or restricted data and must plan for the policy before paying the fee
  • A README, master script, or directory structure needs to be assembled
  • You are unsure what REStat's Data and Code Availability Policy actually requires

The REStat data/code bar (refreshed 2026-06-20; live-check the official policy page)

REStat operates a Data and Code Availability Policy for empirical papers. The signature features that distinguish REStat from its siblings:

  • Deposit to the REStat Harvard Dataverse (dataverse.harvard.edu/dataverse/restat) — REStat uses a proper Dataverse archive, NOT openICPSR (which the AEA journals use) and NOT the JAE Data Archive. Getting the repository right is a load-bearing REStat detail.
  • Post data and code, with documented README files, before publication. The goal is to provide enough information to permit replication of the results in the paper.
  • Proprietary / restricted data: indicate this at submission. When data cannot be posted, you must document the data and provide instructions for how other researchers can obtain it. Practical note: if your paper uses proprietary data, the journal asks you not to pay the submission fee until the editorial office confirms your data comply with the policy.
  • Policy generally applies to papers from volume 92 onward per the REStat Harvard Dataverse API description.

Package architecture (build it as you go)

restat-replication/
  README.(md|pdf)        # the heart of the deposit — see contents below
  data/
    raw/                 # source data (or access instructions if restricted)
    processed/           # built analysis files, regenerated by code
  code/
    00_run_all.do/.R/.py # one master script regenerating EVERY exhibit
    01_build.*           # raw → processed
    02_analysis.*        # processed → estimates
    03_exhibits.*        # estimates → tables/figures
  output/
    tables/  figures/    # exactly what appears in the paper + appendix

README contents (what permits replication)

  • Data availability statement: each dataset, its source, terms, and (if restricted) exact access instructions; flag proprietary data clearly.
  • Computational requirements: software + versions (Stata 18 MP / R 4.x / Python 3.x), packages with versions, OS, approximate run time and hardware.
  • Instructions: how to run 00_run_all from raw data to every table/figure; what each script produces.
  • Mapping: a table linking each exhibit number in the paper/appendix to the script and line that generates it.
  • Seeds: set and report seeds for any simulation / bootstrap / randomization inference.

Checklist

  • Target archive confirmed: REStat Harvard Dataverse (not openICPSR, not JAE)
  • One master script regenerates every table and figure from raw (or processed) data
  • README has data-availability statement, computational requirements, run instructions, exhibit↔script map
  • Software/package versions pinned; seeds set and reported
  • Proprietary/restricted data flagged at submission; access instructions documented
  • (Proprietary data) submission fee not paid until editorial office confirms policy compliance
  • Every number in the paper traces to deposited code (consistency with restat-tables-figures)

Anti-patterns

  • Depositing to openICPSR or the JAE archive — REStat uses its own Harvard Dataverse
  • Treating the package as a post-acceptance chore — assemble it alongside the analysis
  • A README that lists files but gives no run instructions or exhibit↔script mapping
  • Unpinned package versions / unset seeds — results that will not reproduce
  • Discovering only at acceptance that proprietary data cannot be posted (declare at submission)
  • Paying the submission fee on a proprietary-data paper before compliance is confirmed

Output format

【Archive】REStat Harvard Dataverse confirmed? [Y/N]
【Master script】00_run_all regenerates all exhibits from data? [Y/N]
【README】availability stmt + compute reqs + instructions + exhibit↔script map? [Y/N]
【Versions/seeds】software+packages pinned; seeds set/reported? [Y/N]
【Proprietary data】flagged at submission; access instructions; fee held? [Y/N / n/a]
【Traceability】every paper number ← deposited code? [Y/N]
【Next step】restat-referee-strategy

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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