agentsclimarketplace

Review of accounting studies

Skill brycewang-stanford/Awesome-Journal-Skills/English-SocialScience-Journal-Skills/skills/review-of-accounting-studies

Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的 Claude Code/Codex 期刊技能包,从选题、识别策略到表格规范与审稿回复全流程,助你快速发论文。

Install
npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill review-of-accounting-studies

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Use when targeting Review of Accounting Studies (RAST) or deciding whether an accounting manuscript fits this venue. Encodes the journal's fit, framing, method-and-evidence bar, house style, official-submission re-check, and desk-reject heuristics.

SKILL.md

5.5 KB, as published. Nobody here has run it

Review of Accounting Studies (review-of-accounting-studies)

Journal positioning

RAST is a top-tier accounting journal known for rigorous analytical and empirical research, with particular depth in valuation, disclosure, and the information economics of accounting. It is receptive to both well-built analytical models and strong empirical work, and prizes methodological care. Its taste sits close to the economics-based accounting tradition while remaining open across financial-accounting topics. Readership is the research-active financial-accounting and accounting-finance community.

This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current official submission guidelines. Before submitting, re-check the live author instructions on the RAST / Springer site and the submission system.

When to trigger

  • The author names RAST (or the analytical/empirical financial-accounting elite) as the venue.
  • A valuation, disclosure, or information-economics accounting paper — analytical or empirical — needs positioning.
  • An analytically grounded empirical paper whose strength is methods and modeling needs framing.
  • The author needs RAST's desk-reject risks and a credible TAR / JAR / JAE / CAR alternative list.

Scope & topic fit

  • Equity valuation, fundamental analysis, forecasting, and the accounting–value link.
  • Disclosure and information economics: voluntary disclosure, information asymmetry, analysts, and market consequences.
  • Analytical accounting models with empirically relevant implications and the empirical tests that follow them.
  • Earnings, reporting quality, and capital-markets questions with strong design.

Method & evidence bar

  • Methodological rigor is central: empirical work needs credible identification and correct inference; analytical work needs clean, well-motivated models.
  • Strong fit for papers that pair a model with an empirical test, or that make a careful methodological/measurement contribution to valuation or disclosure research.
  • Causal claims require exogenous variation and confounder control; descriptive associations are not enough.
  • Robustness, falsification, and economic interpretation of magnitudes are expected.

Structure & house style

  • The introduction states the valuation/disclosure/information question, the model or design, and the contribution, distinguishing it from the closest prior work.
  • A strong RAST paper integrates theory and evidence and treats methodological choices as load-bearing, not incidental.
  • RAST expects an online appendix for derivations, variable detail, and robustness, with strong data/code transparency.
  • Writing is precise and methods-aware; magnitudes and mechanisms lead over significance stars.

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the official source anchors for this journal family, then cite the current journal-specific page you checked.
  • Search the live site for "Review of Accounting Studies submission guidelines / author instructions" and follow the current Springer version.
  • Re-check formatting, abstract conventions, anonymization, reference style, and the online-appendix/supplementary-materials requirement.
  • Re-check current data and code availability / replication policies and disclosure/ethics requirements.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • One sentence stating the valuation/disclosure/information-economics contribution.
  • The contribution is stated as model / identification / measurement, not as a significant coefficient.
  • Identification, inference, and robustness meet RAST's standards.
  • The introduction positions the paper against recent RAST / top-accounting work.
  • Derivations/online appendix and data/code transparency are ready per the current guide.

Common desk-reject triggers

  • An empirical association with no identification and no information-economics mechanism.
  • An analytical model with no empirically relevant or testable implications.
  • A methodologically careless valuation/disclosure paper.
  • A descriptive paper with no clear contribution to the literature.

Re-routing decision

  • Economics-based archival capital-markets with the highest design bar → journal-of-accounting-research; contracting/disclosure with positive-theory emphasis → journal-of-accounting-and-economics.
  • Broad accounting across methods → the-accounting-review; methodologically pluralistic elite → contemporary-accounting-research.
  • Interpretive/critical/behavioral-in-context → accounting-organizations-and-society.
  • Valuation work that is really asset pricing → journal-of-finance / journal-of-financial-economics; economics-core → a field economics venue.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] Review of Accounting Studies
[Topic tags] <2–3 closest topics>
[Method/evidence] <does the model / identification clear RAST's bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <submission system / online appendix / data-code / disclosure>
[Re-route suggestion] <if not a fit, a better-matched venue>

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.