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

Econometrica

ASecurity

Use when targeting Econometrica or deciding whether an economics manuscript fits this venue. Encodes the journal's fit, framing, method-and-evidence bar, house style, official-submission re-check, and desk-reject heuristics.

1,052 stars
0 votes
0 copies
0 views
Added 6/5/2026
ai-agentsgo

Security Analysis

A100/100

Scanned 6/5/2026

Install to Claude Code

$npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill econometrica --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Econometrica?

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

Security grade badge for Econometrica
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/brycewang-stanford-econometrica/badge)](https://www.skillsdirectory.com/skills/brycewang-stanford-econometrica)

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

Download with Pro
Files
SKILL.md
---
name: econometrica
description: Use when targeting Econometrica or deciding whether an economics manuscript fits this venue. Encodes the journal's fit, framing, method-and-evidence bar, house style, official-submission re-check, and desk-reject heuristics.
---

# Econometrica (econometrica)

## Journal positioning

Econometrica is the journal of the Econometric Society and one of the economics "top-5" (with AER, QJE, JPE, REStud) — the most technical of the five. It publishes econometric theory, economic theory, and highly rigorous structural and empirical work, where the contribution is typically a new theorem, a new identification result, or a new estimator, established to the field's highest formal standard. The readership is technically expert; a paper succeeds on the depth and correctness of its formal contribution, not on topical interest alone.

This skill is a **fit / venue-selection / re-framing** tool. It does not replace the journal's current official submission guidelines. Before submitting, re-check the live author instructions on the Econometric Society / Wiley site and the editorial submission system.

## When to trigger

- The author names Econometrica (or the top-5 with a technical contribution) as the target venue.
- A paper proves new theorems, establishes new identification, or develops a new estimator with full asymptotic theory.
- A structural or empirical paper rests on a genuinely new methodological contribution that needs the most rigorous venue.
- The author needs Econometrica's desk-reject risks and a credible top-5 / methods-journal alternative list.

## Scope & topic fit

- Econometric theory: estimation, inference, identification, asymptotics, nonparametrics, time series, panel, and high-dimensional methods.
- Economic theory: decision theory, game theory, mechanism and market design, general equilibrium, with general theorems.
- Highly rigorous structural econometrics where the identification and estimation argument is itself a contribution.
- Empirical work only when paired with a genuine new method or identification result, not standard applied designs.

## Method & evidence bar

- The formal bar is the filter: theory papers need correct, general theorems with complete proofs; econometrics papers need new identification or estimation results with rigorous large-sample (and where relevant finite-sample) theory.
- Assumptions must be minimal, stated precisely, and economically or statistically motivated; results should generalize beyond a worked example.
- New estimators require consistency, asymptotic distribution, valid inference, and ideally simulation and an empirical illustration.
- Proofs, regularity conditions, and Monte Carlo evidence are expected in heavy supplementary/proof appendices; correctness is non-negotiable.

## Structure & house style

- The introduction states the formal problem, the gap in existing theory, the precise contribution (theorem/estimator/identification result), and how it improves on prior results.
- Definitions, assumptions, propositions, and theorems are stated formally in the main text; long proofs and derivations move to appendices and supplementary material.
- Econometrica enforces a substantial supplementary material / proof appendix and replication standard; an unstructured abstract and JEL codes are standard.
- Notation must be consistent and economical; exhibits (where present) support a method's properties (size, power, coverage) rather than a topical narrative.

## Official-submission checklist

- Before giving submission-ready advice, read `../../resources/source-basis.md` and `../../resources/official-source-map.md`; start from the official source anchors for this journal family, then cite the current journal-specific page you checked.
- Search the live site for "Econometrica submission guidelines" / "information for authors" and the Econometric Society replication and supplementary-material policy, and follow the current versions.
- Re-check the submission fee, LaTeX/formatting requirements, abstract/JEL, anonymization, and supplementary-material/proof-appendix conventions on the submission system.
- Re-check the current data, code, and replication-package deposit policy and any computational-verification workflow before acceptance.
- If the live official instructions conflict with this skill, the official instructions win.

## Pre-submission self-check

- [ ] One sentence stating the new theorem, identification result, or estimator that is the contribution.
- [ ] The contribution is stated as a formal result, not as an empirical finding or statistical significance.
- [ ] The introduction positions the paper against the precise prior theory/econometrics it generalizes or corrects.
- [ ] All proofs are complete and correct; assumptions are minimal and motivated; asymptotics/inference are rigorous.
- [ ] Supplementary material, proofs, and any replication package match the current official guide.

## Common desk-reject triggers

- An applied paper with standard methods and no new theorem, estimator, or identification result.
- A theory result that is a narrow special case, lacks general proofs, or restates known results.
- An estimator proposed without asymptotic theory, valid inference, or simulation evidence.
- Incomplete or incorrect proofs, hidden assumptions, or sloppy formal exposition.

## Re-routing decision

- Rigorous but more topical applied econometrics → `journal-of-econometrics`, `journal-of-applied-econometrics`, `journal-of-business-and-economic-statistics`, or `quantitative-economics`.
- General economic-theory results without the top-5 importance → `journal-of-economic-theory` or `aej-microeconomics`; game theory → `games-and-economic-behavior`.
- General-interest empirical or applied work → `american-economic-review`, `quarterly-journal-of-economics`, or `journal-of-political-economy`.
- Frontier theory/methods with novelty over generality → `review-of-economic-studies`.

## Output format

```text
[Fit] High / Medium / Low (one-line reason)
[Target] Econometrica
[Topic tags] <2–3 closest topics>
[Method/evidence] <does the formal contribution — theorem / estimator / identification — clear Econometrica's bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <submission system / fee / LaTeX / supplementary proofs / replication policy>
[Re-route suggestion] <if not a fit, a better-matched venue>
```

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 →