Skill UI

This comprehensive guide helps authors assemble and audit the Supporting Information (SI) for a Journal of the American Chemical Society (JACS) manuscript. It ensures every reported chemical result and structure is fully reproducible by an independent chemist, covering detailed procedures, full characterization data (NMR, HRMS, IR), stereochemistry, and crystallographic details (CIF/CCDC).

This router guides authors through the complex, multi-stage process of preparing a high-impact chemistry manuscript for the Journal of the American Chemical Society (JACS). It does not replace specialized skills but rather dictates the correct sequence of actions—from scope checking and data framing to revision and final submission—ensuring a rigorous and systematic workflow.

This guide provides comprehensive rules for polishing scientific manuscripts to meet the rigorous standards of the Journal of the American Chemical Society (JACS). It focuses on refining language, ensuring structural clarity, standardizing nomenclature and units, and enforcing 'Claim Discipline' by replacing vague boosters (e.g., 'novel,' 'dramatically improved') with concrete data and quantitative evidence. Ideal for authors whose data is solid but whose prose requires academic refinement.

This guide provides a framework for authors to elevate their research findings beyond mere correlation. It teaches how to articulate a strong, economically significant contribution to journals like JAE by identifying underlying mechanisms, resolving economic tensions, and establishing credible causal links. Ideal for refining introductions and discussions in quantitative academic papers.

A comprehensive framework for conducting rigorous empirical data analysis required for top-tier academic journals. It guides users through building transparent archival samples, specifying appropriate panel data estimators (like firm/year fixed effects), ensuring correct standard error clustering, and executing sophisticated identification strategies (e.g., Difference-in-Differences, Instrumental Variables). Essential for addressing endogeneity and passing deep reviewer scrutiny.

A comprehensive guide for structuring academic manuscripts intended for top-tier journals like JAE. It teaches authors how to transition from merely identifying a research gap to joining and advancing an ongoing, seminal, economics-based scholarly conversation. Key focus areas include capital markets, financial contracting, and disclosure theory.

A comprehensive methodological guide detailing how to design rigorous, publishable empirical or analytical studies for top-tier accounting and economics journals (like JAE). It focuses heavily on achieving causal identification by mastering techniques such as Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity (RDD), and event studies, ensuring the study design credibly supports the economic prediction.

A comprehensive guide for authors revising manuscripts for the Journal of Accounting and Economics (JAE). It details how to structure the point-by-point response letter, emphasizing the critical need to address the editor's concerns and incorporate robust empirical evidence (identification, mechanism, and alternative tests) to satisfy economics-trained reviewers.

A comprehensive guide to the rigorous peer-review process at the Journal of Accounting and Economics (JAE). This skill explains the mandatory editor suitability screen, the double-anonymized review structure, and the finality of the editor's decision. It also details the unique JAE Conference route and provides actionable advice on interpreting decision letters (Reject, Revise and Resubmit).

This comprehensive guide provides authors with a step-by-step workflow for submitting manuscripts to the Journal of Accounting and Economics (JAE) via Elsevier's Editorial Manager. It details crucial requirements, including executing double anonymization, formatting specific metadata (Highlights, JEL codes, Keywords), managing submission fees, and ensuring all files are correctly sequenced for the final review PDF.

This guide outlines the rigorous standards for preparing empirical tables and figures for top-tier academic journals, such as the Journal of Accounting and Economics (JAE). It covers the entire research workflow, including variable definition, sample construction, descriptive statistics, correlation matrices, advanced regressions, and event studies. The goal is to ensure all exhibits are self-contained, reproducible, and meet strict academic reviewer expectations.

This guide provides a rigorous framework for developing robust, theory-driven hypotheses in accounting research, especially for high-impact academic journals. It teaches researchers how to transition from observing mere correlations to formulating hypotheses grounded in established economic theories, such as agency theory, information economics, and positive accounting theory. The process emphasizes identifying the core economic friction, naming the acting agents and their incentives, and deriving directional, falsifiable, and a priori predictions.