Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
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:
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.
| 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 |
Before investing in a draft, answer these in one sentence each; a "no" or "I can't" on any is a fit problem:
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.
【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
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Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.