A skill your agent uses when the identification argument is the bottleneck for a Journal of the European Economic Association (JEEA) manuscript — credible causal identification in an empirical…

MITAuto-check passedResearch & Science

Install Jeea Identification

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jeea-identification -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jeea-identification --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-the-European-Economic-Association-Skills/skills/jeea-identification .claude/skills/jeea-identification && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
jeea-identification
GitHub stars
1.2k
Token cost
~1.7k tokens
SKILL.md length
704 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the identification argument is the bottleneck for a Journal of the European Economic Association (JEEA) manuscript — credible causal identification in an empirical…

  • Parameter identification in a structural/quantitative model
  • SKILL.md covers When to trigger, The JEEA identification bar, Branch paths and Execution bridge (StatsPAI /…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • The source of identification in a theory paper

What it does

Jeea Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the identification argument is the bottleneck for a Journal of the European Economic Association (JEEA) manuscript — credible causal identification in an empirical design, parameter identification in a structural/quantitative model, or the source of identification in a theory paper. Stress-tests the strategy to JEEA's general-interest bar before exhibits are finalized.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Load testing. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Parameter identification in a structural/quantitative model
  • The source of identification in a theory paper

Example prompts

  • “/jeea-identification”

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jeea Identification loads about 1.7k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 704 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 704 words, ~1,729 tokens.

Download SKILL.mdSave it as .claude/skills/jeea-identification/SKILL.md (or your agent's skills folder).
name
jeea-identification
description
Use when the identification argument is the bottleneck for a Journal of the European Economic Association (JEEA) manuscript — credible causal identification in an empirical design, parameter identification in a structural/quantitative model, or the source of identification in a theory paper. Stress-tests the strategy to JEEA's general-interest bar before exhibits are finalized.

Identification Strategy (jeea-identification)

When to trigger

  • An empirical causal claim rests on OLS + controls, or TWFE on staggered timing
  • A structural model's parameters are estimated but it is unclear what in the data identifies them
  • A theory paper's result depends on assumptions whose role is not transparent
  • You are unsure the identification clears JEEA's general-interest theory-and-empirics bar

The JEEA identification bar

JEEA spans theory and empirics, so "identification" means different things by branch — but in every case the mapping from assumptions/data to the object of interest must be explicit and defended, and credible enough for a general-interest readership and a co-editor who is not a subfield specialist. JEEA's house norms reinforce this: report standard errors and confidence sets (no significance asterisks/boldface for significance) and make the empirical strategy reproducible for the JEEA Data Editor's pre-acceptance replication check (DCAS). Pick the branch and make the argument legible.

Branch paths

Branch A: Structural / quantitative identification
  • Name what identifies each parameter. Tie parameters to specific data features / moments; argue identification from the model's structure, not "the estimator converged."
  • Targeted vs. untargeted moments: report fit to targeted moments and untargeted-moment validation as out-of-sample discipline.
  • Sensitivity / informativeness: report parameter sensitivity to moments (sensitivity matrix) so readers see which data move which parameters.
  • Estimation regularity: state the objective (MLE / GMM / MSM / indirect inference), starting values, tolerances, multi-start; report Monte Carlo evidence recovering known parameters.
  • Counterfactual validity: argue the estimated parameters are policy-invariant enough for the counterfactual (Lucas critique).
Branch B: Empirical causal design (applied micro / development / finance)
  • DID / event study: with staggered adoption move beyond TWFE (Callaway–Sant'Anna, Sun–Abraham, de Chaisemartin–D'Haultfœuille); show clean event-study leads; report a Goodman–Bacon decomposition.
  • IV: strong first stage; with weak instruments use Anderson–Rubin / weak-IV-robust sets; defend the exclusion restriction in theory, institutions, and falsification.
  • RDD: Cattaneo–Jansson–Ma density test; optimal bandwidth + robustness; covariate smoothness; bias-corrected CIs.
  • Inference clustered at the assignment level; address few-cluster issues (wild-cluster bootstrap).
Branch C: Theory / mechanism identification
  • What assumptions do the work. Identify the minimal assumptions driving the headline result; show which can be relaxed and which are essential.
  • Comparative statics as identification: make clear which primitive moves which prediction, so the model's empirical content is testable.
  • Source of the result: distinguish a genuinely new mechanism from a re-parameterization; route to jeea-theory-model for generality and proof discipline.
Branch D: Experimental / own-data
  • Pre-registration in a recognized registry; report deviations and the explicit estimand.
  • Randomization balance; attrition (Lee bounds if differential); multiple-hypothesis adjustment; external-validity discussion.
Show full SKILL.md (299 more words)Show less

Execution bridge (StatsPAI / Stata MCP)

Estimate and audit the design, don't only describe it. Full map: execution-with-mcp. JEEA is a general-interest European economics flagship; credible identification across applied fields.

  • detect_design → recommend → fit with as_handle=true → audit_result.
  • Observational causal claims: staggered DiD (callaway_santanna / sun_abraham + bacon_decomposition + honest_did_from_result); IV (effective_f_test + anderson_rubin_ci); RDD (rdrobust + mccrary_test).
  • Experiments: randomization-based inference + romano_wolf for many-outcome control.
  • Sensitivity: oster_delta / sensemakr for observational claims.

Report the magnitude in interpretable units; route the full battery to the appendix. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.

Checklist

  • Branch chosen; the assumption/data-to-object mapping stated in one sentence
  • Structural: each parameter tied to identifying moments; sensitivity + Monte Carlo recovery shown
  • Empirical: design-appropriate diagnostics (pre-trends / density / first-stage / balance); modern estimator where TWFE would bias
  • Theory: minimal assumptions named; what is essential vs. relaxable made explicit
  • Inference reported as SEs / confidence sets (no asterisks); clustering/assignment level correct
  • The claim never exceeds what the identification supports

Anti-patterns

  • "The estimator converged" presented as if it were identification (structural)
  • TWFE on staggered treatment with no heterogeneity-bias discussion (empirical)
  • A theory result whose driving assumption is hidden in notation, so its empirical content is unclear
  • Calibrating parameters and running a counterfactual without arguing policy-invariance
  • Reporting significance with asterisks instead of standard errors / confidence sets

Referee pushback mapped to the identification fix

  • "This is OLS with controls dressed up as causal." → Provide a design (DID/IV/RDD) or a credible selection-on-observables defense with sensitivity (Oster) and falsification.
  • "Staggered TWFE here is biased." → Re-estimate with Callaway–Sant'Anna or Sun–Abraham; show flat event-study leads.
  • "Your structural estimates are calibration in disguise." → Show the sensitivity matrix and which moment moves which parameter; report untargeted fit.
  • "The model's headline result is an artifact of one assumption." → Name the assumption, relax it, and show the result survives (or scope it honestly).

Output format

【Branch】structural / empirical / theory / experimental
【Assumption-or-data-to-object mapping】one sentence
【Identification evidence】[moments+sensitivity / pre-trends+density+first-stage / minimal-assumptions / balance]
【Estimation/inference】objective + SEs/confidence sets (no asterisks); clustering if any
【What it does NOT identify】[...]
【Next step】jeea-theory-model or jeea-robustness

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Journal-of-the-European-Economic-Association-Skills/skills/jeea-identification of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

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Questions about Jeea Identification

What does Jeea Identification do?

A skill your agent uses when the identification argument is the bottleneck for a Journal of the European Economic Association (JEEA) manuscript — credible causal identification in an empirical…. Jeea Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the identification argument is the bottleneck for a Journal of the European Economic Association (JEEA) manuscript — credible causal identification in an empirical design, parameter identification in a structural/quantitative model, or the source of identification in a theory paper.

When should I use Jeea Identification?

Jeea Identification fits situations like: parameter identification in a structural/quantitative model; the source of identification in a theory paper.

How do I install Jeea Identification in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jeea-identification -a claude-code`. Or copy the skill folder (Journal-of-the-European-Economic-Association-Skills/skills/jeea-identification in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jeea-identification in your project. Claude Code loads it when a task matches its description.

How do I install Jeea Identification in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jeea-identification -a codex`. Or copy the skill folder (Journal-of-the-European-Economic-Association-Skills/skills/jeea-identification in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jeea-identification in your project. Codex loads it when a task matches its description.

Can I use Jeea Identification in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jeea-identification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jeea-identification, .gemini/skills/jeea-identification, .github/skills/jeea-identification and .opencode/skills/jeea-identification in your project.

What does Jeea Identification need to run?

SKILL.md names no scripts, command-line tools or credentials: Jeea Identification is instructions for the agent only.

Does Jeea Identification access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Jeea Identification safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Jeea Identification use?

Jeea Identification is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Jeea Identification use?

About 1.7k tokens (SKILL.md is roughly 6.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Jeea Identification?

Skills that share tags, products or a category with Jeea Identification: What If Oracle (K-Dense-AI/scientific-agent-skills, 48k stars), Paper Review (EvoScientist/EvoSkills, 475 stars), Data Finder (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars) and Weakness Scanner (flonat/flonat-research, 145 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jeea Identification?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.