Use when deciding whether a microeconomics project fits the American Economic Journal: Microeconomics (AEJ: Micro) rather than JET, GEB, Theoretical Economics, Econometrica, or AEJ: Applied. Tests scope and broad-interest fit; it does not develop the model (see aejmic-theory-model).
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
AEJ: Micro is the AEA's quarterly journal for microeconomic theory and its applications, founded 2009. It is theory-first but values broad microeconomic interest delivered through the AEA editorial process. The fit question is two-pronged: (1) is the contribution a theory contribution (a model, result, characterization, or theory-grounded experiment)? and (2) is the result broadly interesting to micro economists, not only to specialists in one technique?
| Your contribution is primarily… | Likely best home |
|---|---|
| A clean, broadly interesting micro-theory result | AEJ: Micro |
| A maximally general or highly technical theory advance | JET / GEB |
| A new solution concept / methodological foundation | Theoretical Economics / Econometrica |
| An empirical applied-micro finding | AEJ: Applied |
| A theory-grounded experiment testing a model | AEJ: Micro (or a field/experimental venue) |
| A structural IO paper where the model delivers the insight | AEJ: Micro (or QE / a field journal) |
A draft characterizes optimal disclosure in a two-seller search market and also tests one comparative static in a lab experiment. Is it AEJ: Micro? Yes if the characterization is the contribution and the experiment is supporting evidence — that is theory-first with broad IO/information interest. It drifts to a field journal if the experiment becomes the headline and the model is decorative, and toward JET if the authors chase maximal generality at the cost of the economic message.
【Contribution type】theory result / theory-grounded experiment / structural-with-theory
【One-sentence claim】[...]
【Broad-interest check】who beyond specialists cares, and why
【Sibling boundaries cleared】JET-GEB? TE-Econometrica? AEJ:Applied? metrics? [Y/N each]
【JEL codes】[primary; secondary]
【Verdict】AEJ: Micro fit? [yes / reconsider venue]
【Next step】aejmic-literature-positioning, then aejmic-theory-model
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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.
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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.