jeg-replication-and-data-policy
GitHub用于准备《经济增长杂志》的数据可用性声明、复现代码及校准文件。涵盖实证数据、历史资料与GIS层，确保符合Springer Nature政策，提供标准化目录结构与审计记录以保障研究可重复性。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jeg-replication-and-data-policy -g -y
SKILL.md
Frontmatter
{
"name": "jeg-replication-and-data-policy",
"description": "Use when preparing Journal of Economic Growth (JEG) data availability statements, replication code, calibration files, digitized historical sources, GIS layers, and Springer Nature research-data documentation for empirical, quantitative, or theoretical growth and comparative-development papers."
}
Replication & Data Policy (jeg-replication-and-data-policy)
When to trigger
- The paper uses empirical growth data, historical data, simulations, or calibration code
- You need a Data Availability Statement for Springer Nature
- Data are public, proprietary, restricted, or author-constructed
Policy stance
JEG follows Springer Nature research-data policy: original research articles need a Data Availability Statement. A journal-specific mandatory data editor or code archive was not confirmed in the source map, but reproducible materials are still expected for credible growth work.
Package checklist
- Data README with sources, access dates, licenses, and restrictions.
- Code pipeline that regenerates tables and figures.
- Calibration file listing parameter values and sources.
- Public repository or DOI for shareable data/code when allowed.
- Restricted-data instructions and contact/access procedure when data cannot be redistributed.
Growth package layout
Use a structure that separates empirical and model artifacts:
replication/
README.md
data_sources.md
code/
calibration/
output_tables/
output_figures/
manuscript_map.md
manuscript_map.md should list each table/figure, the script that creates it, the input data or
calibration file, and the expected output path. For theory-only papers, include the scripts that create
numerical examples, calibration tables, or transition-path figures.
Calibration/data audit
For each calibrated or empirical object, record:
Object | Source | Transformation | Moment/target | Script | Manuscript location
This catches common growth-paper replication failures: undocumented historical series, country-code harmonization drift, purchasing-power or deflator choices, calibration targets that do not match the reported table, and transition-path scripts that cannot be rerun from a clean checkout. If data are constructed by hand from historical sources, include the transcription notes and source images or access instructions when permissions allow.
Historical and geospatial documentation duties
Deep-determinants packages carry failure modes beyond a standard code archive:
- Digitized historical sources: archive the scan references, transcription rules, and the share of pages double-entered for error checking; record the holding archive and license for every map or census volume.
- GIS layers: state the projection/CRS, raster resolution, and the construction chain (e.g., least-cost-path cost-surface parameters); ship shapefiles, or exact download instructions when redistribution is barred.
- Boundary harmonization: include the crosswalk between historical polities and modern units with the rule applied to split or merged units — referees at this venue do re-run persistence results on alternative crosswalks.
- Distance and terrain variables: the build script matters more than the variable itself; one undocumented cost-surface assumption can move headline coefficients.
Worked vignette — packaging a deep-roots paper
Illustrative inventory for a manuscript instrumenting institutions with a historical shock across 1,800 districts:
data_sources.mdlists 6 sources: two public cross-country series, one digitized 19th-century census (scans archived, license noted), one proprietary geocoded survey (access instructions only, no raw deposit), and two constructed GIS rasters with full build scripts.manuscript_map.mdcovers 9 exhibits, each tied to a script; Table 3's Conley standard errors are flagged as depending on the spatial-weights script with a fixed seed.- The known-gap note records that the survey vendor forbids redistribution; the Data Availability Statement says so and points to the application procedure — confirm the exact statement wording against the journal's current author guidelines.
Deposit decision rules
- Public secondary data → deposit extracts plus build code; cite the original source DOI.
- Author-digitized historical data → deposit the dataset and transcription notes; at this journal that dataset is often the paper's most durable contribution.
- Proprietary or restricted data → deposit code plus a masked or synthetic sample where the license allows, and document the access path step by step.
- Simulation/calibration-only papers → deposit the full solver and parameter files so every transition path regenerates exactly from a clean checkout.
Output format
[Data status] public / restricted / proprietary / simulated / mixed
[Statement draft] ...
[Code archive] ...
[Calibration files] ...
[Gaps before submission] ...
[Next step] jeg-submission
Version History
- 1839142 Current 2026-07-05 13:33
