Skill UI

This tool guides researchers through the critical initial phase of academic manuscript preparation. It tests whether a research question has genuine accounting relevance, a credible source of identifying variation (e.g., policy shock, rule change), clear economic stakes, and sufficient marginal contribution for top-tier accounting journals like JAR. It serves as a methodological fit check before any data collection begins.

This guide assists researchers in assembling a comprehensive, reproducible data and code supplement for submissions to statistical journals, adhering to the American Statistical Association (ASA) data-sharing policies. It outlines the required structure (README, code, data), provenance tracking, environment pinning, and necessary steps (like setting random seeds and drafting data availability statements) to ensure that published results can be fully regenerated and verified by reviewers.

This framework guides authors in transforming raw empirical findings into compelling academic contributions suitable for top-tier finance journals. It teaches how to sharpen the focus from merely presenting 'better data' to articulating the underlying financial mechanism, institutional friction, or policy implication, ensuring the research answers the critical question of 'why it matters.'

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 authors preparing artifacts (code, data, models, etc.) for submission to the Journal of Computer-Aided Design & Computer Graphics (JCAD&CG). It details best practices for ensuring research reproducibility, writing honest availability statements, and managing artifacts during the double-blind review process, focusing on ethical standards regardless of specific journal policy.

A comprehensive guide for authors submitting to the Journal of Corporate Finance (JCF). It details how to comply with Elsevier's Option C data availability requirements, focusing on drafting the data availability statement and structuring the research archive. It provides best practices for handling licensed, proprietary data (e.g., Compustat, CRSP) by recommending the sharing of construction code and access instructions, rather than raw data deposits.

This guide assists researchers in sharpening the development-economics takeaway of their manuscripts. It helps authors move beyond merely stating coefficients to explicitly defining the core contribution—the mechanism, policy implication, or theoretical lesson—that the work delivers to the field of development economics, ensuring the work's significance is unmistakable.

A comprehensive guide detailing the mandatory replication and data policy required by journals like JDE. It outlines how to build a self-contained, reproducible package containing master scripts, documented data provenance, pinned environments, and strategies for handling restricted or proprietary data, ensuring readiness for review and acceptance.

This guide helps researchers rigorously vet their academic questions against the standards of top-tier development economics journals. It teaches users to identify 'first-order' issues focused on low- and middle-income economies, ensuring the research mechanism genuinely contributes to understanding poverty, growth, and policy levers for poor populations, rather than merely being a general micro-economic result.

A specialized structural review pass designed to polish academic manuscripts for top development economics journals like the Journal of Development Economics (JDE). It guides authors to ensure the narrative emphasizes the core development question, quantifies findings with magnitudes, and clearly articulates policy implications for development policymakers and academic readers.

A comprehensive guide for establishing robust causal links in environmental economics. It covers advanced econometric techniques for policy evaluation, including staggered Difference-in-Differences (DiD), Instrumental Variables (IV), and Regression Discontinuity Designs (RDD). It specifically addresses challenges in non-market valuation, such as spatial sorting, hypothetical bias, and separating weather shocks from long-term climate trends, ensuring the recovered parameter is welfare-relevant.

A comprehensive guide for academics writing in environmental economics, detailing how to articulate the marginal contribution of a manuscript. It teaches authors to move beyond simply presenting new data or methods, focusing instead on identifying the specific environmental-economic gap, policy parameter, or mechanism that the field currently lacks.