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.
日本語の概要は準備中です。原文の説明を表示しています。
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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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
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。