jhr-replication-and-data-policy

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Use when preparing Journal of Human Resources data and replication materials: archive plan footnote, public repository deposit, CC0 license, Data Availability Statement, read-me file, waiver requests, RCT pre-analysis-plan statements, and code package.

brycewang-stanford By brycewang-stanford schedule Updated 6/10/2026

name: jhr-replication-and-data-policy description: Use when preparing Journal of Human Resources data and replication materials: archive plan footnote, public repository deposit, CC0 license, Data Availability Statement, read-me file, waiver requests, RCT pre-analysis-plan statements, and code package.

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

When to trigger

  • The paper is being prepared for JHR submission or acceptance
  • You need the archive-plan footnote, Data Availability Statement, or waiver
  • Data are restricted, proprietary, administrative, or RCT-based

JHR policy core

JHR's data policy is unusually concrete: accepted papers must preserve data and post replication materials in a well-curated public repository where possible, with a public-domain CC0 1.0 Universal license. At submission, include an archive plan footnote with a persistent link if available, or request a waiver at initial submission.

Package contents

  • Data files that can legally be shared
  • Code and models needed to reproduce all tables and figures
  • Read-me file explaining the sequence
  • Data Availability Statement on the title page
  • Restricted-data access instructions or waiver justification
  • For RCTs: pre-analysis plan registration and deviations

Waiver logic

Request a waiver at initial submission when data cannot be publicly deposited. State how other researchers can obtain the data and commit to provide reasonable guidance.

Restricted-data package

When the data cannot be public, still prepare:

  • synthetic or public-use data that exercises every script path when possible;
  • data dictionary with variable construction and source tables;
  • access instructions, application links, and approval constraints;
  • log showing which outputs require restricted data;
  • archive-plan footnote explaining the waiver and reproducibility route.

Deposit decisions by data source

Data source What can usually be deposited Waiver posture
Public-use surveys (CPS, ACS, NLSY, PSID extracts) Extraction code plus the analysis file, or code that rebuilds it from raw downloads Rarely needed; check redistribution terms of each survey
State administrative records (UI wages, K-12, Medicaid) Code, codebooks, aggregate exhibits; microdata stays with the agency Waiver expected; document the access route precisely
Own RCT microdata De-identified analysis files under CC0 where consent and IRB allow Partial waiver for identifying fields; PAP registration stated
Proprietary/commercial data Code, pseudo-data, purchase or license instructions Waiver with a named acquisition path
Linked or matched files Each source assessed separately; the crosswalk is often the binding constraint Mixed: deposit what is public, waiver the link keys

Repository choice and licensing details evolve — confirm against the journal's current author guidelines before depositing.

Worked waiver scenario: UI wage records

Illustrative case: earnings outcomes come from one state's unemployment-insurance wage records under a data-use agreement that bars any microdata release.

  1. Footnote at submission: names the agency, the agreement, and states that code, codebooks, and a synthetic test file will be archived under CC0.
  2. The read-me lists the application steps and typical approval constraints a replicator faces, and which exhibits need the restricted extract.
  3. Every script runs against the synthetic file end-to-end so reviewers can verify logic without the data.
  4. The Data Availability Statement mirrors the footnote — the two must not drift apart between submission and acceptance.

Read-me skeleton for the JHR archive

README
  1. Data sources & access (public files included; restricted: how to apply)
  2. Software & versions (Stata/R/Python; packages pinned)
  3. Run order: 00_master -> 01_clean -> 02_analysis -> 03_exhibits
  4. Runtime & hardware notes; random seeds fixed where used
  5. Exhibit map: each table/figure -> producing script -> data requirement
  6. License: CC0 1.0 Universal (data and code deposited)

Pre-acceptance dry run

  • Clone the package to a clean directory and run it without manual edits.
  • Confirm every main-text and appendix exhibit regenerates byte-stable or with documented stochastic variation.
  • Check that no intermediate file under a restrictive license leaks into the deposit.

Output format

[Data status] public / restricted / proprietary / confidential / mixed
[Archive plan footnote] ...
[DAS] ...
[Waiver needed] yes/no + reason
[RCT PAP status] ...
[Next step] jhr-submission
Install via CLI
npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills --skill jhr-replication-and-data-policy
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