| name | restat-replication-package |
| description | 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 â the deposit to the REStat Harvard Dataverse with a README that permits replication. Builds the package; it does not run the primary analysis. |
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) â 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 â 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 â processed
02_analysis.* # processed â estimates
03_exhibits.* # estimates â 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
Anti-patterns
- Depositing to openICPSR or the JAE archive â REStat uses its own Harvard Dataverse
- Treating the package as a post-acceptance chore â assemble it alongside the analysis
- A README that lists files but gives no run instructions or exhibitâscript mapping
- Unpinned package versions / unset seeds â 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
ăArchiveăREStat Harvard Dataverse confirmed? [Y/N]
ăMaster scriptă00_run_all regenerates all exhibits from data? [Y/N]
ăREADMEăavailability stmt + compute reqs + instructions + exhibitâscript map? [Y/N]
ăVersions/seedsăsoftware+packages pinned; seeds set/reported? [Y/N]
ăProprietary dataăflagged at submission; access instructions; fee held? [Y/N / n/a]
ăTraceabilityăevery paper number â deposited code? [Y/N]
ăNext stepărestat-referee-strategy