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wber-replication-package【数据与研究】Use when assembling the data and code replication package for a The World Bank Economic Review (WBER) manuscript to meet WBER's condition-of-publication data/code release, the data availability statement with a DOI repository link, and the realities of restricted developing-country data. Builds the deposit and README; it does not run the analysis or …
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WBER's most distinctive, stable policy is transparency as a condition of publication: authors must, where ethically and legally possible, publicly release all data and the software code underlying a published paper. By repute WBER is the only development field journal that routinely publishes data and code, and this fits the broader World Bank reproducible-research push. The manuscript must carry a data availability statement — on the title page / author-affiliation footnote — with a persistent (preferably DOI) link to the data in a repository (检索于 2026-06;以官网为准; verify exact wording on the OUP author guidelines). Build the package as you analyze; do not treat it as an acceptance-day formality.
| Component | Requirement |
|---|---|
| Data files | All data used, in open/documented formats; or, for restricted data, a precise documented access path |
| Analysis + transformation code | Every script from raw → cleaned data → each table/figure |
| Master script | One run_all that regenerates every exhibit from raw inputs |
| README | Data sources, access terms, computational requirements, run instructions, and an exhibit-to-code map |
| Data Availability Statement | On the title page; persistent DOI link to the repository deposit |
| Instruments | Survey instruments / enumerator manuals for own-data field studies |
This is the WBER-specific hard part — much development data is governed by national statistics offices, ministries, or data providers (LSMS, DHS, census, tax records):
version + recorded ssc/net package versions; requirements.txt/conda env (Python); renv.lock (R).code/05_main.do, Figure 2 → code/06_event_study.R.Adapt the vendored skeleton in
../../resources/code/(master → clean → descriptive → DiD/IV/RD → mechanism → robustness → tables) as the package backbone.
run_all master script regenerates every table and figure from raw dataA poverty paper uses LSMS consumption data (restricted, registration-gated) plus a public price index. The team cannot post the LSMS microdata, so the package contains: every cleaning and analysis script; a README naming the specific LSMS country, round, and version and the exact registration steps a replicator must complete; a small synthetic extract with the same variable structure so run_all executes end-to-end; documented deflators and PPP factors; and pinned Stata package versions with seeds set for the bootstrap. The title page carries a data availability statement with a DOI link to the openICPSR-style deposit holding the code and synthetic data. Because the public price index can be shared, it is deposited in full. The package would let a verifier reproduce the logic, and reproduce the numbers entirely once they obtain LSMS access.
【Master script】run_all regenerates all exhibits from raw? [Y/N]
【Data】all deposited, or restricted path + synthetic extract? [state]
【DAS + DOI】title-page statement with persistent repository link? [Y/N]
【Survey provenance】DHS/LSMS/admin round + version + access step cited? [Y/N]
【Reproducibility】versions pinned + seeds + no absolute paths + clean run? [Y/N]
【Currency】deflators/PPP/FX documented? [Y/N]
【Restricted/exemption】declared early? [Y/N/NA]
【Next step】wber-referee-strategy
../../resources/code/ — reproducible Stata + Python skeleton to adapt as the package backbone../../resources/official-source-map.md — official OUP / WBER URLs behind the data policy