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ectheory-skills

Twelve-skill bundle covering the Econometric Theory (ET) manuscript lifecycle, from theorem-driven topic selection through single-anonymous review and rebuttal.

1,413 on GitHubby Bryce Wangv1.1.0MITupdated 1 month agoacademic
/

Plugin ectheory-skills from marketplace awesome-journal-skills in brycewang-stanford/Awesome-Journal-Skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (12)

  • ectheory-contribution-framing

    Use to frame the central result of an Econometric Theory (ET) paper so its generality and importance are legible — stating the theorem and its scope up front, choosing Article vs Miscellanea framing, and matching the new editorial program's themed directions.

  • ectheory-data-analysis

    Use for the Monte Carlo and numerical-illustration component of an Econometric Theory (ET) paper — designing simulations that show finite-sample behavior tracks the asymptotics, plus any illustrative empirical example. Lighter than empirical journals; the spine stays the theory.

  • ectheory-identification-strategy

    Use when the assumptions, regularity conditions, and asymptotic results are the bottleneck for an Econometric Theory (ET) theorem-proof paper — adapt "identification" to mean stating defensible assumptions, proving the limit theory, and establishing generality, not causal design.

  • ectheory-literature-positioning

    Use to stake an Econometric Theory (ET) contribution against the existing theory frontier — which assumptions you weaken, which limit result you generalize, what was previously unproven — using APA author-date citations, not a standalone literature survey.

  • ectheory-rebuttal

    Use when an Econometric Theory (ET) decision letter arrives and a response strategy and letter are needed — handling proof-checking referee objections, fixing assumptions and gaps, and using the online Supplement, then writing a point-by-point response. It structures the revision, not the proofs the

  • ectheory-replication-and-data-policy

    Use to handle reproducibility and the supplementary-material file for an Econometric Theory (ET) paper — ET has no mandatory data/code archive (theory journal); the relevant policy is the voluntary online Supplementary Material for already-reviewed proofs, derivations, and simulation evidence.

  • ectheory-review-process

    Use to understand and prepare for the Econometric Theory (ET) review process — single-anonymous refereeing (reviewers see the author), the Article/Miscellanea/ET-Interview article types, and war-gaming the proof-checking referee before submitting.

  • ectheory-submission

    Use when running the final pre-submission preflight for Econometric Theory (ET) via ScholarOne / Manuscript Central — single embedded-font PDF, single-anonymous (no double-blind anonymization), APA author-date references, the 50-page ceiling, the optional cover letter, and the Supplementary Material

  • ectheory-tables-figures

    Use for the exhibits in an Econometric Theory (ET) paper — Monte Carlo size/power/coverage tables, finite-sample and limit-behavior plots, with self-contained notes, ET figure-format specs (TIFF/EPS/PDF), and legibility at 50% reduction.

  • ectheory-topic-selection

    Use when deciding whether a result is the right kind of contribution for Econometric Theory (ET) — a general, foundational econometric-theory result (asymptotics, proofs, theorems) rather than an applied estimate, and whether it fits a full Article or a short Miscellanea.

  • ectheory-workflow

    Use as the router for an Econometric Theory (ET) manuscript — decides which ectheory-* skill to invoke next across the theorem-proof lifecycle, from topic selection through single-anonymous review and rebuttal. Start here when unsure where you are.

  • ectheory-writing-style

    Use to polish the prose, notation, and proof exposition of an Econometric Theory (ET) manuscript — theorem-proof clarity, consistent notation, APA author-date references, and ET manuscript-prep specs (11pt, 1.5 spacing, 1.25in margins, 200-word abstract, 40-char running head).

View source on GitHub copaper.ai

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