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ecta-replication-package

Use when assembling the code and data deposit for an Econometrica manuscript under the journal's Data and Code Availability Policy, including reprod…

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技能内容

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

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