Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Qe Replication And Data Policy

ASecurity

Use to assemble a Quantitative Economics (QE) replication package that passes the Econometric Society Data Editor's pre-acceptance reproducibility check — raw data, code, documentation, README, and any exemption requests — under the DCAS-compatible ES Data and Code Availability Policy (NOT the JAE archive). Builds and audits the package; it does not run the estimation.

1,052 stars
0 votes
0 copies
1 views
Added 6/6/2026
ai-agentsdocumentation

Security Analysis

A100/100

Scanned 6/6/2026

Install to Claude Code

$npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill qe-replication-and-data-policy --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Qe Replication And Data Policy?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Qe Replication And Data Policy
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/brycewang-stanford-qe-replication-and-data-policy/badge)](https://www.skillsdirectory.com/skills/brycewang-stanford-qe-replication-and-data-policy)

More formats (shields.io, HTML) on the badges page.

Download with Pro
Files
SKILL.md
---
name: qe-replication-and-data-policy
description: Use to assemble a Quantitative Economics (QE) replication package that passes the Econometric Society Data Editor's pre-acceptance reproducibility check — raw data, code, documentation, README, and any exemption requests — under the DCAS-compatible ES Data and Code Availability Policy (NOT the JAE archive). Builds and audits the package; it does not run the estimation.
---

# Replication & Data Policy (qe-replication-and-data-policy)

## When to trigger

- You are preparing data and code for a QE submission or an accepted paper
- You need to know exactly what the ES Data Editor checks and when
- Some data are proprietary or restricted and you need to plan an exemption
- You want the package built so the pre-acceptance reproducibility check passes on the first pass

## The QE / Econometric Society replication regime (verified 2026-06-01)

QE follows the **Econometric Society Data and Code Availability Policy**, shared across *Econometrica*, *Quantitative Economics*, and *Theoretical Economics* and **compatible with DCAS** (the Data and Code Availability Standard). Key facts:

- The Society publishes empirical / experimental / simulation papers **only if data and code are clearly documented and non-exclusive** to the authors.
- **Before acceptance**, authors must provide **raw data, code, and documentation** sufficient to **replicate all results** in the paper and approved online appendices.
- The **ES Data Editor** (inaugural Data Editor **Joan Llull**) conducts **reproducibility checks before final acceptance**. Partial-check scope must be **documented in the README**.
- Replication / supplementary materials are **posted with the article**.
- For **long-running or hard-to-access computations**, simplified/manageable versions and **summary output files** are encouraged.
- Any request for **exemption or limits on data/code access** must be **stated at initial submission** and is at editor discretion.

> **Important:** QE uses this **centralized ES system and the ES Data Editor Website**, **NOT** the JAE (Journal of Applied Econometrics) Data Archive. Do not prepare a JAE-style deposit.

## Building the package

1. **Raw data** (or, for restricted data, the access pathway + the code that would run on it) plus all intermediate data-build steps.
2. **Code** that runs end to end: one master script (`run_all`) regenerating every table, figure, and number from raw inputs.
3. **Documentation / README**: data sources and licenses, software and exact versions, hardware/run-time notes, the mapping from scripts to exhibits, seeds, and **any partial-check scope**.
4. **Environment pinning**: `renv.lock`, `requirements.txt`/`conda`, `Project.toml`/`Manifest.toml`, recorded Stata `ssc`/`net` versions.
5. **Heavy computations**: include manageable versions and summary output files so the Data Editor can verify without re-running everything.
6. **Experimental/own-data**: include instructions/survey transcripts and the pre-registration reference (effective Jan 1, 2026).

## Proprietary / restricted data
- State the exemption or access-limit request **at initial submission** (not at acceptance).
- Provide all **code** even when raw data cannot be shared, plus instructions to obtain access and synthetic or sample data where possible.
- Document exactly which results the Data Editor can and cannot reproduce, in the README.

## Checklist

- [ ] Raw data + full build pipeline included (or restricted-data access path + code)
- [ ] One master script regenerates every result from raw inputs
- [ ] README maps scripts to exhibits; lists sources, versions, seeds, run times
- [ ] Environment pinned across all languages used
- [ ] Heavy computations have manageable versions + summary output files
- [ ] Any exemption / access limit stated at initial submission
- [ ] Partial-check scope documented in the README
- [ ] Built against the **ES Data Editor** regime (DCAS), not the JAE archive

## Anti-patterns

- Preparing a JAE Data Archive deposit by mistake (QE uses the ES system)
- Leaving the package until acceptance — the reproducibility check is **before** acceptance
- Code that depends on absolute local paths or unpinned package versions
- Requesting a proprietary-data exemption only at acceptance instead of at submission
- A README that does not map scripts to the specific tables and figures

## Output format

```
【Regime】ES Data and Code Availability Policy (DCAS) — NOT JAE archive
【Data】raw + build pipeline included? (or restricted-data path + code) [Y/N]
【Master script】regenerates all results from raw? [Y/N]
【README】sources/versions/seeds/script-to-exhibit map? [Y/N]
【Heavy computation】manageable version + summary outputs? [Y/N or N/A]
【Exemption】stated at initial submission? [Y/N or N/A]
【Next step】qe-review-process (pre-acceptance Data Editor check)
```

Attribution

brycewang-stanfordbrycewang-stanford
View sourceMore from brycewang-stanford →
SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Related Skills

Caveman

Ultra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".

1066601 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

686011 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3351 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

651 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →