技能 数据科学 AEJ经济政策论文适用性评估

AEJ经济政策论文适用性评估

v20260724
aejpol-topic-selection
本指南帮助研究人员评估其实证经济学论文是否符合《AEJ: Economic Policy》的发表要求。核心在于指导用户将单纯的经验发现,提升至围绕一个具有广泛福利或成本效益意义的政策问题进行构建和论证。
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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
信息
Category 数据科学
Name aejpol-topic-selection
版本 v20260724
大小 5.77KB
更新时间 2026-07-28
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