Replication Package

Produce the deposit an economist hands a journal at acceptance: a directory tree (data/, code/, output/, README) plus a DCAS compliance checklist, built to the AEA Data and Code Availability Standard, openICPSR deposit expectations, and the Social Science Reproduction Platform reproduction protocol. This skill moves the repo from auditing reproducibility to producing the deposit — /audit-reproducibility proves the numbers; this skill packages everything a third party needs to regenerate them from scratch.

Core principle: the package is reproducible by a stranger with the data and the README — no tacit knowledge, no "ask the author" steps. Every table and figure maps to the exact script and line that produces it.

When to use

• At acceptance. The journal's data editor (AEA, REStud, JPE, EJ, ...) requests a DCAS-compliant deposit before the paper is typeset.
• Before an openICPSR / Zenodo / Dataverse upload. Build the tree and README once, locally, before the web upload.
• Pre-submission dry run. Catch the "I never wrote down where Table 3 comes from" gap while it is cheap to fix.
• Confidential-data papers. Produce the access-restricted-data note and a runnable-on-restricted-data package even when the data itself cannot be deposited.

Inputs

• $0 — path to the manuscript (.tex, .qmd, .md, .pdf). Required (the source of the Table/Figure inventory).
• $1 — outputs directory. Defaults to scripts/R/_outputs/. Recognised alternatives: scripts/stata/_outputs/, scripts/python/_outputs/, _targets/objects/.

Workflow