Agent Skills
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ecta-replication-package
GitHub用于构建符合Econometrica期刊政策的数据与代码可复现包，确保蒙特卡洛模拟及实证数据可重现。包含代码、主脚本、种子、环境配置及README，并指导提交至Zenodo进行存档和审核。
Trigger Scenarios
准备符合Econometrica数据与代码可用性政策的提交材料
需要确保蒙特卡洛表格或实证结果可从干净签出中精确复现
论文处于接受/最终文件阶段且需通过数据编辑者的可复现性验证
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecta-replication-package -g -y
SKILL.md
Frontmatter
{
"name": "ecta-replication-package",
"description": "Use when assembling the code and data deposit for an Econometrica manuscript under the journal's Data and Code Availability Policy, including reproducible Monte Carlo and (for empirical work) data provenance. Builds and audits the replication package; it does not design the simulations (use ecta-robustness) or format exhibits (use ecta-tables-figures)."
}
Replication Package (ecta-replication-package)
When to trigger
- You are preparing the deposit required under the Data and Code Availability Policy
- Monte Carlo tables cannot be regenerated bit-for-bit from a clean checkout
- An empirical paper has no documented data provenance or access path
- You are at acceptance / final-files stage and the Data Editor will verify reproducibility
Econometrica (and the other Econometric Society journals) enforce a single ES-wide Data and Code Availability Policy. Concrete, Econometrica-specific specifics that differ from the AER/AEJ (AEA Data Editor + openICPSR) pipeline:
- The policy applies to papers with empirical, experimental, and/or simulation results. A pure-theory paper with no such results is effectively exempt — but any requested exemption or limitation on data/code availability must be stated at initial submission (the handling Co-Editor decides; exemptions are not considered later).
- Reproducibility is verified before final acceptance by the Econometric Society Data Editor team. In practice you submit final files at Conditional Acceptance to a separate Editorial Express account for the Data Editor's checks and correspondence.
- The package must include a README in PDF; the Social Science Data Editors' README template is recommended and covers every required item.
- For packages conditionally accepted after July 1, 2023, the replication package is deposited at the Econometric Society Journals' Community at Zenodo (you may reserve a DOI in advance). Another trusted open repository with a permanent DOI can satisfy the requirement with Data Editor approval — but not the AEA/openICPSR route by default.
Verify the current policy text and deposit location on the official ES Data Editor site before finalizing — the specifics evolve.
Build the package as you go, not the night before final files. A package assembled from memory at the end almost never reproduces — and here a real human Data Editor will run it.
What the package must contain
| Component | Requirement |
|---|---|
| Code | All scripts that produce every table, figure, and number in the paper and Supplemental Material |
| Master script | One command (run_all) regenerates every exhibit end to end |
| Random seeds | Every stochastic step seeded and recorded, so Monte Carlo tables reproduce bit-for-bit (simulations are covered by the ES policy) |
| Environment | Software, version numbers, and pinned dependencies (Docker / renv / conda / Project.toml) |
| README (PDF) | Hardware, expected runtime, data sources, file-by-file description, exhibit ↔ script map; use the Social Science Data Editors' README template |
| Data (empirical) | The data, or — when proprietary/restricted — exact provenance and an access path that lets a replicator obtain it |
| Deposit | The Econometric Society Journals' Community at Zenodo (after the Data Editor's checks; reserve a DOI in advance), unless a trusted DOI repository is approved |
| License / terms | Any data-use restrictions documented; redistribution rights respected |
Reproducibility discipline for Monte Carlo
- Seed everything and record the seed alongside each table. Re-running must reproduce the exact numbers, not merely "similar" ones.
- Master script runs all simulations and writes outputs to named files that map to table numbers.
- Runtime honesty. State how long the full simulation takes and on what hardware; if it is days, provide a smaller smoke-test path that runs quickly and a way to verify the full run.
- No manual steps. No "then copy the number into the table by hand" — exhibits should be generated programmatically where feasible.
Empirical data provenance
- Public data: include it (or a script that downloads a fixed version) plus the citation.
- Proprietary / restricted data (e.g., licensed firm-level, confidential admin data): you generally cannot redistribute it. Document the exact source, version, access procedure, required licenses/fees, and contact, so a replicator can obtain the same data. Provide all code, and where allowed, a synthetic or example dataset that exercises the pipeline.
- Confidentiality: strip personal identifiers; respect data-provider agreements; state any approvals obtained.
Recommended structure
replication/
README.md # provenance, environment, runtime, exhibit↔script map
run_all.{do,R,py,jl} # master script: one command rebuilds everything
code/ # numbered scripts (setup → simulate/estimate → tables → figures)
data/ # public data or a synthetic example; provenance for restricted data
output/ # generated tables/figures (regenerable, not hand-edited)
env/ # Dockerfile / renv.lock / environment.yml / Project.toml
Checklist
- Every table, figure, and number (paper + Supplemental Material) regenerated by code
- Single master script reproduces everything end to end
- Every random draw seeded; Monte Carlo tables reproduce bit-for-bit (simulations are in-scope)
- Environment pinned (versions + dependencies)
- README in PDF (Social Science Data Editors' template) documents hardware, runtime, data sources, and exhibit↔script map
- Public data included or downloaded by script with a fixed version
- Restricted data: provenance + access path documented; synthetic example provided if allowed
- Any exemption/limitation requested at initial submission (theory paper with no empirical/experimental/simulation results may be exempt)
- Deposit plan: Econometric Society Journals' Community at Zenodo (DOI reserved); Data Editor checks pass at conditional acceptance
- Confidentiality and data-use terms respected; identifiers removed
- Verified against the current ES Data and Code Availability Policy and Data Editor site
Anti-patterns
- Unseeded simulations, so tables only reproduce "approximately"
- A pile of scripts with no master file and undocumented run order
- Numbers transcribed into tables by hand, untraceable to any script
- "Data available on request" with no provenance, version, or access procedure
- An environment that only runs on the author's machine (unpinned versions)
- Redistributing proprietary data in violation of the license
- Leaving package assembly to the final-files deadline
Output format
【Package status】complete / gaps
【Master script】present / missing
【Seeds recorded】yes/no — bit-for-bit reproducible: yes/no
【Environment pinned】yes/no (tool: ...)
【Data】public-included / restricted-provenance-documented / theory-exempt / MISSING
【Exhibit↔script map】complete / gaps: [...]
【Deposit】Zenodo (ES Journals' Community) DOI reserved: yes/no
【Policy check】verified against current ES Data Editor policy: yes/no
【Next step】ecta-referee-strategy
Version History
- 1839142 Current 2026-07-05 12:52
