Skill UI

A comprehensive guide for finalizing the core evidence—tables and figures—for high-stakes empirical accounting or economics papers (e.g., Journal of Accounting Research). It outlines the mandatory 'exhibit set,' covering sample construction, descriptive statistics, correlation matrices, main regression results, and crucial identification plots (DiD, RD). Focuses on adhering to rigorous house styles and ensuring all claims are data-supported.

A comprehensive guide detailing best practices for creating clear, rigorous, and publication-ready tables and figures for advanced statistical or econometric manuscripts. It ensures that complex results (such as size-power curves, bias/RMSE comparisons, and empirical payoffs) are legible to both expert statisticians and applied economists, improving presentation without altering the underlying results.

This tool guides users through the rigorous scope requirements for submitting research to the Journal of Business & Economic Statistics (JBES). It ensures that a project possesses both methodological novelty and clear empirical relevance, particularly in microeconomics, macroeconomics, business, and finance. It serves as a critical sanity check, preventing submissions that are purely theoretical or purely applied without methodological contribution.

This comprehensive guide outlines the best practices for preparing a complete and reproducible research package for submission to the Journal of Banking & Finance (JBF) following Elsevier Option C guidelines. It details requirements for data availability statements, proper structuring of code and data access materials, and best methods for managing proprietary or restricted datasets (such as CRSP or Compustat), ensuring research transparency and verifiability.

A comprehensive guide for structuring and polishing empirical tables and figures for top-tier academic journals, such as the Journal of Business Venturing (JBV). It covers the standards for presenting descriptives, main model coefficients, interaction plots, survival curves, process models, and qualitative data structures. This skill ensures exhibits are self-contained, interpretable, and adhere to rigorous academic house styles.

This comprehensive guide assists users in analyzing and reporting data for high-impact academic journals, specifically following the rigorous standards of the Journal of Consumer Research (JCR). It covers advanced statistical process evidence (mediation, moderation, effect sizes) for behavioral experiments, as well as methods for establishing trustworthiness in interpretive (CCT) research. It emphasizes transparency, replication code, and adherence to modern research reporting mandates.

Provides a comprehensive guide for designing rigorous academic studies for high-impact journals. Whether planning multi-study behavioral experiments, interpretive Consumer Culture Theory (CCT) fieldwork, or mixed designs, this resource ensures that the evidence collected is optimally structured to support the conceptual claim, emphasizing internal validity and transparency.

This guide details the rigorous and developmental peer review process of the Journal of Consumer Research (JCR). It covers the structure (double-anonymization, co-editor roles), reviewer expectations (conceptual contribution, evidence rigor, data transparency), and how to interpret decision letters (Reject vs. R&R). Use it before submission or when receiving a decision to structure your rebuttal and revision plan effectively.

This guide provides best practices for presenting empirical results in development economics, emphasizing a 'figure-forward' approach suitable for top-tier journals. It teaches researchers how to transform complex statistical models (like DID, RDD, and ITT) into clear, self-contained, and impactful visual exhibits (plots and maps). The goal is to ensure that the headline findings are immediately legible to expert referees, moving beyond traditional, complex coefficient tables.

A comprehensive guide designed to stress-test the causal identification of behavioral mechanisms for top-tier economic journals (e.g., JEBO). It provides stringent criteria across lab/field experiments, observational data (DiD, IV, RDD), and simulations, ensuring the design isolates the claimed psychological or institutional channel, not just a correlation. Use this when standard econometric methods are insufficient to prove mechanism causality.

A comprehensive guide to structuring robustness checks for behavioral economics and empirical research. Instead of merely listing statistical tests, this framework mandates organizing checks by the underlying behavioral threat (e.g., experimenter demand, multiple comparisons, specification choice). It provides specific guidelines for experiments, observational data, and simulations, ensuring that findings are robust against alternative behavioral explanations and methodological choices.

Provides comprehensive guidelines for meeting modern academic publishing standards, particularly those required by educational psychology journals. It outlines mandatory requirements for ensuring research reproducibility, including depositing data, materials, and analysis code in trusted repositories with persistent identifiers (DOIs), adhering to JARS reporting standards, and documenting preregistration status.