Skill UI

A comprehensive guide for strengthening causal identification strategies (DID, IV, RDD, RCT) for high-stakes academic publications. It details modern econometric estimators, required diagnostic checks (pre-trends, density tests, weak-IV robustness), and the philosophical shift from technique to answering a big economic question, essential for submitting to top journals like the Quarterly Journal of Economics (QJE).

This guide provides detailed best practices for presenting empirical results, specifically tailored for top-tier economics journals like the QJE. It emphasizes shifting from 'table-heavy' to 'figure-forward' visualization, covering techniques for event-study plots, RDD discontinuity plots, and ensuring all exhibits are self-contained, readable, and follow strict academic formatting standards.

This tool guides researchers through pressure-testing their economic research ideas against the standards of top-tier, general-interest journals (like QJE). It helps diagnose whether a study's 'big idea' and broad implications are compelling enough, ensuring the focus is on the general lesson rather than just the technical method or narrow finding. Ideal for structuring academic arguments and improving manuscript scope.

This skill polishes scholarly prose, abstracts, and introductions to align with the narrative-driven, ambitious style of the Quarterly Journal of Economics (QJE). It focuses on making the core research contribution immediately legible to a general-interest, non-specialist reader, ensuring the big idea lands fast, even in long-form empirical papers. The skill guides users on structuring the 'introduction arc,' stating findings with concrete numbers, and minimizing technical jargon.

A comprehensive guide for drafting persuasive and structured author responses to major academic conference reviews. This methodology teaches how to triage critical concerns, anchor answers strictly to submitted evidence (tables, appendices, repository), and effectively counter common technical pushbacks such as baseline tuning, temporal data leakage, and offline-online gaps, ensuring the response is professional, anonymous, and high-impact.

A comprehensive guide for structuring the Related Work section for top-tier recommender systems conferences (RecSys). It advises authors on auditing novelty by positioning their contribution against adjacent research fields (e.g., SIGIR, KDD, WSDM), addressing critical lines (like reproducibility and off-policy evaluation), and ensuring the work is technically distinct from prior or concurrent studies.

This comprehensive preflight guide ensures authors meet all technical and procedural requirements before submitting to academic journals, specifically detailing the steps for the Review of Economic Dynamics (RED). It covers mandatory steps such as confirming submission fees, adhering to strict formatting rules (abstract length, citation style), preparing data archives (Option C), and navigating the journal's specific workflow (ScienceDirect/Editorial Manager). Following this checklist minimizes rejection risks due to formatting or procedural errors.

This comprehensive skill guides authors targeting Research Policy. It details the journal's scope, required evidence standards, house style, and common publishing pitfalls. It helps authors frame their work to fit the interdisciplinary field of innovation studies (STI), covering topics from R&D and technology policy to economic implications.

This comprehensive guide details advanced econometric methodologies required for rigorous causal inference studies. It covers how to defend both the causal identification strategy (DiD, RD, IV) and the quality of variables (handling measurement error, index construction). Learn to meet the stringent standards of top-tier journals by applying techniques like staggered DiD estimators, density testing, and attenuation correction.

This guide is designed for advanced academic research, helping scholars evaluate whether their current research idea meets the rigorous standards of top-tier economics journals (e.g., REStud). It teaches how to distill complex findings into a single, original, and technically excellent contribution, diagnosing potential weaknesses in novelty, scope, and general interest.

A comprehensive guide for executing rigorous empirical accounting studies. This resource details best practices for advanced econometric techniques, including correct standard error clustering (firm-level, two-way clustering), executing identification strategies (DiD, RD, IV/2SLS), validating accounting constructs, and performing extensive robustness checks (falsification, placebo tests). It also emphasizes data provenance and reproducibility, critical for top-tier academic publications.

A comprehensive guide for establishing credible causal inference in accounting and finance research. This methodology covers advanced techniques including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity (RDD), and experimental design. It instructs users on how to move beyond simple controls, defining the specific identifying variation necessary for publishing rigorous, causality-focused academic work.