A skill your agent uses when the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a…

MITAuto-check passedResearch & Science

Install Ecopol Identification

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

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ecopol-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/Economic-Policy-Skills/skills/ecopol-identification .claude/skills/ecopol-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
ecopol-identification
GitHub stars
1.2k
Token cost
~1.6k tokens
SKILL.md length
705 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 an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a…

  • The identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect
  • SKILL.md covers When to trigger, The EP identification bar, Branch A: Empirical causal… and Branch B: Structural /…, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Parameter identification in a quantitative policy model

What it does

Ecopol Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a quantitative policy model. Stress-tests it to the EP bar (credible to an academic discussant, legible to a policy discussant) before exhibits are finalized.

Its SKILL.md is about 1.6k 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

  • The identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect
  • Parameter identification in a quantitative policy model

Example prompts

  • “/ecopol-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

Ecopol Identification loads about 1.6k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 705 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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). 705 words, ~1,619 tokens.

Download SKILL.mdSave it as .claude/skills/ecopol-identification/SKILL.md (or your agent's skills folder).
name
ecopol-identification
description
Use when the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a quantitative policy model. Stress-tests it to the EP bar (credible to an academic discussant, legible to a policy discussant) before exhibits are finalized.

Identification Strategy (ecopol-identification)

When to trigger

  • A policy effect rests on OLS + controls, or TWFE on staggered policy rollout
  • An IV's exclusion restriction is institutional hand-waving, not an argument
  • A structural/quantitative policy model is estimated but it is unclear what in the data pins each parameter
  • The counterfactual policy scenario relies on parameters whose policy-invariance is undefended
  • You must convince two discussants at once — one who will probe the econometrics, one who needs the design to be legible enough to trust the policy number

The EP identification bar

EP papers are debated by two named discussants and read by policymakers, so identification must be both rigorous and legible. The academic discussant will apply the modern frontier; the policy discussant must be able to follow why the estimate is causal without reading the appendix. The discipline: make the mapping from data/variation to the policy claim explicit in the main text in plain language, and carry the formal defense in a technical appendix (EP's house split — accessible main text, rigorous appendix). Because results feed a policy recommendation, the magnitude — not just the sign or the stars — must be defended; report standard errors and confidence intervals, never lean on significance asterisks for the headline claim.

Branch A: Empirical causal design (most EP papers)

  • DID / event study: with staggered policy adoption, move beyond TWFE — Callaway–Sant'Anna, Sun–Abraham, or de Chaisemartin–D'Haultfœuille. Show a clean event-study with pre-trends; a Goodman–Bacon decomposition pre-empts the "negative-weights" discussant.
  • IV: strong first stage (report it); with weak instruments use Anderson–Rubin / weak-IV-robust sets. Defend exclusion in three registers — theory, institutions, and a falsification test — because the policy discussant trusts institutional logic.
  • RDD: density test (McCrary / Cattaneo–Jansson–Ma), data-driven bandwidth + robustness, covariate smoothness, bias-corrected CIs. State who is at the cutoff and whether they are the policy-relevant population.
  • Inference: cluster at the policy-assignment level; address few-cluster problems (wild-cluster bootstrap) — many EP designs have few treated jurisdictions.

Branch B: Structural / quantitative policy model

  • Name what identifies each parameter — tie it to a data moment, not "the estimator converged."
  • Targeted vs. untargeted moments: report fit to targeted moments and validate against untargeted ones as out-of-sample discipline.
  • Counterfactual policy-invariance: the whole point of EP is the counterfactual policy. Argue (Lucas-critique style) that the estimated parameters are invariant to the policy you simulate; if they are not, say so and bound it.
  • Numerical credibility: state the objective (MLE/GMM/MSM), multi-start for the global optimum, tolerances; report Monte Carlo recovery of known parameters.
Show full SKILL.md (302 more words)Show less

Translate the design for the policy reader

For each design, write the one-sentence plain-language version that goes in the main text: e.g. "Because the reform applied only to firms just above a 50-employee threshold, firms just below serve as a control group — so the difference in their hiring is the reform's effect." The appendix carries the formal estimand and assumptions.

Execution bridge (StatsPAI / Stata MCP)

Estimate and audit the design, don't only describe it. Full map: execution-with-mcp. Economic Policy is policy-facing applied economics; foreground a credible design and a policy-relevant magnitude.

  • 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

  • One plain-language sentence in the main text: what variation identifies the policy effect
  • Modern estimator where TWFE would bias (staggered rollout) + clean event-study leads
  • IV: first stage reported; exclusion defended in theory + institutions + falsification
  • RDD: density + bandwidth robustness + bias-corrected CIs; cutoff population is policy-relevant
  • Structural: each parameter tied to a moment; counterfactual policy-invariance argued
  • Inference clustered at assignment level; few-cluster correction if needed
  • Headline magnitude reported with SE/CI; the policy claim never exceeds what identification supports

Anti-patterns

  • TWFE on staggered policy timing with no heterogeneity-bias discussion (the academic discussant pounces)
  • An exclusion restriction stated only as "plausibly exogenous" with no institutional or falsification backing
  • Running a counterfactual policy scenario on parameters whose invariance is never defended
  • Hiding the entire identification argument in the appendix so the policy discussant cannot follow the causal story
  • Headlining a policy recommendation off a starred coefficient without reporting the magnitude and its CI

Output format

text
【Journal】Economic Policy (EP)
【Skill】ecopol-identification
【Branch】empirical causal / structural-quantitative
【Plain-language identification】one sentence for the policy reader
【Frontier diagnostics】[event-study + Bacon / first-stage + AR / density + bandwidth / moments + invariance]
【Inference】SE/CI + clustering level (no asterisk-driven headline)
【What it does NOT identify】[...]
【Next skill】ecopol-theory-model

© 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 Economic-Policy-Skills/skills/ecopol-identification of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

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Data Finderbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~1.7kAutomated safety check: PassCustom licence
Weakness Scannerflonat/flonat-research146—~1.5kAutomated safety check: PassMIT
Ecta Identificationfranklee16/academic-research-skills2231 repos~1.9kAutomated safety check: PassNone

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Questions about Ecopol Identification

What does Ecopol Identification do?

A skill your agent uses when the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a…. Ecopol Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a quantitative policy model.

When should I use Ecopol Identification?

Ecopol Identification fits situations like: the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect; parameter identification in a quantitative policy model.

How do I install Ecopol Identification in Claude Code?

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

How do I install Ecopol Identification in Codex?

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

Can I use Ecopol 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 ecopol-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/ecopol-identification, .gemini/skills/ecopol-identification, .github/skills/ecopol-identification and .opencode/skills/ecopol-identification in your project.

What does Ecopol Identification need to run?

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

Does Ecopol 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 Ecopol 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 Ecopol Identification use?

Ecopol 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 Ecopol Identification use?

About 1.6k tokens (SKILL.md is roughly 6.5k 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 Ecopol Identification?

Skills that share tags, products or a category with Ecopol Identification: What If Oracle (K-Dense-AI/scientific-agent-skills, 48k stars), Paper Review (EvoScientist/EvoSkills, 476 stars), Data Finder (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars) and Weakness Scanner (flonat/flonat-research, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ecopol Identification?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.