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aejpol-topic-selection

Use when deciding whether a project fits AEJ: Economic Policy rather than J. Public Economics, AEJ: Applied, or AER, and when sharpening the policy question and its welfare stake for an AEJ: Economic Policy manuscript.

Install / Use

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejpol-topic-selection

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

85/100

Supported Platforms

Universal

Our assessment of aejpol-topic-selection

aejpol-topic-selection scores 85/100 on our quality scale, 2230th of 4,610 Development & Engineering skills we index (top 49%).

Its SKILL.md is 5.7 KB long, well organised into 11 sections with 1 code example: a solid amount of guidance for an agent.

With 1,158 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
17/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 18 days ago, so aejpol-topic-selection is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

aejpol-topic-selection compared with similar skills

All 4 of these similar skills score higher than aejpol-topic-selection; compare them before choosing.

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aejpol-topic-selection (this skill)by brycewang-stanford851.2k18d agoSKILL.md
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Frequently asked questions

How do I install aejpol-topic-selection?
Run npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejpol-topic-selection. The install tabs above show the steps for each supported agent.
Which AI agents does aejpol-topic-selection work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is aejpol-topic-selection safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is aejpol-topic-selection still maintained?
The repository was last updated 18 days ago, so aejpol-topic-selection is actively maintained.

name: aejpol-topic-selection description: Use when deciding whether a project fits AEJ: Economic Policy rather than J. Public Economics, AEJ: Applied, or AER, and when sharpening the policy question and its welfare stake for an AEJ: Economic Policy manuscript. Frames fit and the policy-question-first contribution; it does not design the identification or run estimation.

Topic Selection & Policy-Question Fit (aejpol-topic-selection)

When to trigger

  • You have a clean empirical result but are unsure it is "an AEJ: Policy paper"
  • The project could plausibly go to J. Public Economics, AEJ: Applied, or AER and you must pick
  • A referee or colleague says the question is "narrow," "not a policy paper," or "so what?"
  • You can state a finding but not yet a policy question with a welfare / cost-benefit / distributional stake

The AEJ: Policy bar — lead with the policy question

AEJ: Policy publishes the economic analysis OF policy: a paper is built around a policy question ("should this tax / mandate / subsidy / regulation exist, expand, or change, and at what welfare cost?") whose answer carries a welfare, cost-benefit, or distributional implication of broad interest to the AEA readership. Two halves must both be present from the first page:

  1. A real policy lever. A specific instrument someone could pull — a credit, a tax schedule, an eligibility rule, an emissions standard, a transfer, a mandate, an enforcement regime. Not just "an interesting natural experiment."
  2. A counterfactual / welfare reading. What changes, for whom, and is it worth it — a cost-benefit ratio, a marginal-value-of-public-funds (MVPF), an incidence/distributional split, or a calibrated welfare number. A clean estimate with no policy reading is off-fit.

Policy areas in scope

Public economics & taxation · environmental & energy · health · education · labor & social insurance · regulation & antitrust · development policy · political economy of policy. Empirical (quasi-experimental / RCT) and applied-theory work both fit — provided the policy question and welfare relevance are explicit.

Fit decision table (route by the dominant pull)

| If the paper is mainly… | It belongs at… | Tell | |---|---|---| | broad-interest policy question + credible causal evidence + welfare reading | AEJ: Policy | the policy lesson is the headline | | a deep field-public-finance contribution for specialists | J. Public Economics | broad readership would not follow the "so what" | | identification-driven applied micro with no policy lever / welfare claim | AEJ: Applied | the natural experiment, not a policy, is the point | | a first-order, general-interest result warranting top-5 length | AER | the contribution is larger and longer than a field-leading policy paper |

Checklist

  • [ ] The policy lever is named in one sentence (instrument + who is affected)
  • [ ] The policy question is stated as a question with a welfare/cost-benefit/distributional stake
  • [ ] The counterfactual is concrete (what the policy is compared against)
  • [ ] Broad-interest test passed: a non-specialist AEA reader sees why it matters
  • [ ] Sibling check done (not JPubE field-only / not AEJ:Applied no-policy / not AER-scale)
  • [ ] You can name the welfare object you will eventually report (MVPF, cost-per-X, incidence)

Anti-patterns

  • "We exploit a clean natural experiment" with no policy the experiment evaluates (reads as AEJ: Applied)
  • A field-public-finance result with no broad-interest framing (reads as J. Public Economics)
  • A descriptive or correlational "policy-relevant" topic with no credible counterfactual
  • Promising a welfare/cost-benefit reading you have no way to compute
  • Leading with the dataset or method instead of the policy question

Three questions that decide fit fast

Before investing in a draft, answer these in one sentence each; a "no" or "I can't" on any is a fit problem:

  1. The lever test — can you name the instrument a decision-maker would pull? (If it is "a shock," not a policy, lean AEJ: Applied.)
  2. The welfare test — can you name the welfare object you will report (MVPF, cost-per-X, incidence)? (If not, the policy "so what" is missing.)
  3. The broad-interest test — would a non-specialist AEA reader, not just the field, care about the answer? (If only the field cares, lean JPubE.)

Worked vignette (illustrative)

A draft estimates that a state's expansion of a childcare subsidy raised maternal employment. As "we find subsidy → employment" it is a clean applied-micro result (AEJ: Applied). Reframed for AEJ: Policy: "Is expanding the childcare subsidy a cost-effective way to raise maternal labor supply, and who bears the cost?" — now the employment elasticity feeds a cost-per-additional-worker and an incidence split across income groups (illustrative), and the paper has a policy lever, a counterfactual, and a welfare reading.

Referee pushback mapped to the fix

  • "Better suited to a field journal." → Sharpen the broad-interest framing; lead with the policy lesson, not the institutional detail.
  • "This is just a clean natural experiment." → Name the policy the experiment evaluates and the welfare object; if there is none, reconsider the target.
  • "Interesting but so what for policy?" → Add the cost-benefit / incidence reading to the abstract, not the conclusion.

Output format

【Policy lever】instrument + affected population (one sentence)
【Policy question】stated as a question with a welfare/cost-benefit/distributional stake
【Counterfactual】what the policy is compared against
【Welfare object to report】MVPF / cost-per-X / incidence / calibrated welfare
【Fit verdict】AEJ: Policy vs JPubE / AEJ:Applied / AER + one-line reason
【Next step】aejpol-literature-positioning

Related Skills

View on GitHub
GitHub Stars1.2k
CategoryDevelopment
Updated18d ago
Forks153

Languages

Stata

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions