Skill UI

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.

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.

This guide assists researchers in transforming vague datasets or observations into robust, positive, and economics-driven research questions suitable for prestigious accounting journals (like JAE). It teaches key concepts, such as identifying economic friction, distinguishing between normative and positive questions, establishing plausible identification strategies, and mapping the topic to specific academic domains.

This comprehensive router guides researchers through the entire process of developing, analyzing, and submitting a manuscript to the Journal of Accounting and Economics (JAE). It provides a structured roadmap, helping users determine the next critical step—from initial topic selection and theory development to advanced econometrics, contribution framing, and final submission preparation. It ensures that the work maintains a rigorous, economics-based argument using archival data, preventing common pitfalls like vague ideas or insufficient identification strategies.

A comprehensive guide for researchers on sharpening the theoretical contribution of academic manuscripts, especially for specialized journals like JAIS. It teaches authors how to transition from describing 'what they did' to articulating 'what the field now knows,' ensuring the work is generative, challenging, and structurally aligned with its chosen category (Theory, Empirical, etc.).

This guide provides comprehensive methodological advice for academic submissions in Information Systems (IS), particularly for journals like JAIS. It covers selecting and rigorously defending diverse research designs—including behavioral experiments, causal inference (Economics of IS), design science, qualitative studies, and literature reviews. Use it when you need to validate the suitability of your methodology against your research claims and underlying phenomena.

A comprehensive guide detailing best practices for creating self-contained, professional, and publication-ready exhibits (tables, figures, matrices) for scholarly manuscripts. It emphasizes making the body text standalone, adhering to journal-specific styles (e.g., APA, JAIS), and presenting complex data (like SEM results) clearly for rigorous peer review.

This comprehensive guide provides a rigorous framework for developing original theoretical contributions in Information Systems (IS) research, particularly for top-tier academic journals. It outlines various theoretical genres—including behavioral mechanisms, economic models, and design theories—and teaches authors how to move beyond mere description. Key principles include constructing novel, well-defined constructs; identifying clear boundary conditions; and executing deep 'round-trip' theoretical integrations to ensure the contribution is genuinely original.