jeg-replication-and-data-policy

Documents

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.

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Source SKILL.md: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/Journal-of-Economic-Growth-Skills/skills/jeg-replication-and-data-policy/SKILL.md

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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.md lists 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.md covers 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