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 deciding whether an applied-micro project belongs at the American Economic Journal: Applied Economics (AEJ: Applied) rather than AER, AEJ: Economic Policy, or a field journal, and what its central question should be. Sets venue fit and question scope; it does not design the identification (see aeja-identification).
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
AEJ: Applied wants empirical applied microeconomics where a credible causal research design answers a substantive economic question of broad applied-micro interest — above a pure field journal but more specialized than AER. Use this decision table to place the project.
| Signal in your project | Likely fit |
|---|---|
| Clean identification + a question labor/dev/health/ed/public economists all care about | AEJ: Applied (core) |
| Same design but the contribution is mainly a policy verdict / program ROI framing | lean AEJ: Economic Policy |
| Genuinely general-interest, agenda-setting, methodologically ambitious, long | aim AER first |
| Contribution is field-internal (only sub-field specialists will cite it) | a field journal (JHE / JOLE / JDE) |
| New estimator with a toy application | Econometrica / REStud / JoE, not AEJ: Applied |
AEJ: Applied is empirical-first: theory appears to interpret and discipline the estimate, not to lead. A descriptive or measurement paper can fit if the question is sharp and the measurement is the contribution — but it must not overclaim causality.
aeja-identification).A researcher has linked administrative tax and education records for one country and wants to "study inequality." That is a dataset, not a question. Working through the fit test: the cleanest variation in the data is a school-finance reform that changed per-pupil spending at a sharp formula threshold — an RD. The question becomes "what is the effect of marginal school spending on adult earnings, identified by the funding-formula discontinuity?" Two subfields beyond education (labor and public) will cite it; the imaginable headline is "a $1,000 increase in per-pupil spending raises adult earnings by ~___%." Now it is AEJ: Applied-shaped — and clearly not an AER agenda paper or an AEJ: Policy program verdict.
【Question】one sentence, estimand + population named
【Venue verdict】AEJ: Applied because [not AER: ___] [not AEJ: Policy: ___] [not field: ___]
【Cross-field appeal】subfields that will cite: [..., ...]
【Headline (anticipated)】"X raises/lowers Y by ~___ (units)"
【Design seed】RCT / DID / RD / IV / shift-share / descriptive
【JEL draft】[codes]
【Next step】aeja-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.
中文简介正在准备中。当前显示原文说明。
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.
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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.
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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.
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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.
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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.
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