ectj-topic-selection
GitHub用于评估计量经济学论文是否适合发表在《The Econometrics Journal》。依据包括方法是否具有突破性、应用价值及紧凑格式要求，并指导将其路由至其他更合适的期刊如Econometric Theory或领域期刊。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ectj-topic-selection -g -y
SKILL.md
Frontmatter
{
"name": "ectj-topic-selection",
"description": "Use when deciding whether an econometrics paper fits The Econometrics Journal's leading-case, applied-value bar rather than Journal of Econometrics, Econometric Theory, Quantitative Economics, Review of Economics and Statistics, or a field journal."
}
EctJ Topic Selection
Use this before drafting. EctJ is not a generic repository for any econometric technique; it asks for original econometrics with direct or potential applied value and a leading-case contribution.
Fit test
- Prefer EctJ when the paper gives a path-breaking or leading-case method, estimator, test, identification result, or applied-econometrics design that can travel beyond one narrow dataset.
- Require an empirical application even for theory papers; do not treat Monte Carlo evidence as a substitute for applied relevance.
- Route to Econometric Theory if the contribution is almost entirely formal and needs longer theorem development.
- Route to Journal of Econometrics if the paper is broader, longer, or more exhaustive than EctJ's compact format supports.
- Route to a field journal if the econometric novelty is mainly a tool for a substantive economics result.
Borderline routing rules
- Choose EctJ when the contribution is a sharp method with direct applied value and can be taught as a leading case within the compact format.
- Choose Econometric Theory when the proof architecture, generality, or theorem development is the main contribution and needs more formal space.
- Choose Journal of Econometrics when the contribution is broad, exhaustive, or method-family defining rather than a focused leading case.
- Choose a field journal when the economic result matters more than the method, and the method would be a technical appendix elsewhere.
If the application can be removed without changing the paper's value, EctJ fit is weak. If the theorem can be removed without changing the paper's value, EctJ fit is also weak.
Shape of an accepted EctJ methods paper
Calibration anchors, hedged where practice varies: the modal accepted structure is a compact chain — motivation through an econometric failure, the leading-case theory, a Monte Carlo section summarized within about a page of main text, and an empirical illustration that changes a real decision — inside the roughly 20-page printed format, with full grids and secondary material in the online appendix where the rules permit. Papers that allocate half their pages to a literature survey or to institutional background do not match the venue's shape even when technically strong. For early-career authors, the Royal Economic Society's Denis Sargan Econometric Prize, awarded for the best EctJ article by a young author, is one more signal that the venue wants sharp leading-case work rather than encyclopedic treatments.
Worked fit scoring
Vignette (illustrative): a paper derives an estimator for staggered-adoption designs when untreated potential outcomes follow an unobserved factor structure.
- Leading case: two factors, balanced panel — sharp and teachable. EctJ-positive.
- Applied value: re-estimates a published minimum-wage application and reverses one headline conclusion (illustrative: the pooled effect changes sign at the 10% level). EctJ-positive.
- Empirical application: present and diagnostic, not decorative. EctJ-positive.
- Length pressure: full proofs need 30 printed pages. EctJ-negative — either restructure the proofs for the printed appendix or route to a longer-format econometrics journal.
Three positives and one repairable negative reads as possible EctJ with compression to fix first, not as a venue switch.
Scope traps specific to this venue
- A method whose applied value exists only in one proprietary dataset fails the travel test; the EctJ application should be reproducible under the replication policy, so a public or accessible dataset materially raises fit.
- Topics already exhaustively treated in long-format econometrics journals fit only if the paper finds a genuinely new leading case, not a cleaner exposition.
- Machine-learning-assisted econometrics fits when the economic parameter and its inference guarantees are the contribution; a prediction-accuracy paper without an econometric object belongs in an ML venue.
- Pure comparison or replication studies are usually off-shape here; the venue asks for original methodology with demonstrated use.
Output format
[Fit] strong EctJ / possible EctJ / better elsewhere
[Leading case] <methodological or applied-econometrics advance>
[Applied value] <empirical domain and why it matters>
[Routing risk] <too narrow, too theoretical, too empirical, too long>
[Next action] <theory, application, framing, or venue switch>
Version History
- 1839142 Current 2026-07-05 14:30
