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