Skill UI

This guide helps researchers determine if their project's core contribution is genuinely centered on recommender systems. It provides a structured fit test to route the work to the most appropriate top-tier venue (RecSys, SIGIR, KDD, etc.) and select the correct conference track before starting the writing process.

A comprehensive project management skill designed for academic submissions in Recommender Systems (RecSys). It guides users through the entire research lifecycle, from initial venue fit and data freezing to abstract submission, full paper writing, anonymous repository management, rebuttal drafting, and final camera-ready preparation. It provides backward-planning time offsets and risk identification.

This comprehensive guide helps authors structure the inferential backbone of economic papers for top journals. It provides detailed checklists for theoretical models (assumptions, regularity), empirical studies (causal design, identification), and computational methods (convergence, asymptotics), ensuring claims are robust and credible across different paper types.

This guide establishes the rigorous policy for submitting computational and empirical papers to academic journals. It mandates that authors provide sufficient data, source code, and detailed documentation (including execution order, random seeds, and OS used) to ensure that research findings can be fully reproduced by others, adhering to global standards like Option C.

This guide helps researchers precisely define the marginal contribution (the 'delta') of their academic work. Instead of writing a general literature tour, it instructs authors to compare their findings directly against 3-5 most proximate prior papers, emphasizing specific advancements in identification or measurement. It is crucial for submissions to high-stakes journals.

This guide outlines the comprehensive policy and architecture required for submitting a fully reproducible replication package to The Review of Economics and Statistics (REStat). It details how to structure the repository, including data, master scripts, and the README file, ensuring that every result can be traced and regenerated by other researchers.

A comprehensive framework designed for rigorous academic research, ensuring that primary findings remain stable across various methodological choices. It systematically tests the robustness of estimates against potential weaknesses in specification, sample selection, measurement, identification, and inference. This suite defends the headline result against skeptical scrutiny, which is crucial for publication in top-tier economics journals.

A methodological guide for empirical economists on balancing theoretical depth with empirical findings. It advises authors on how to structure models—determining if a structural, light, or minimal theory dose is appropriate—to ensure the core contribution remains the testable estimate, rather than the theory itself.

This guide provides a rigorous framework for stress-testing and implementing state-of-the-art causal identification strategies required for high-impact empirical economics. It covers advanced methodologies including Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity (RDD), Synthetic Control, and Structural Modeling. It emphasizes modern estimators (e.g., Callaway-Sant'Anna, effective F) and robust diagnostic checks to ensure the causal claims are methodologically sound and defensible.

This skill guides the writing of a strong, argumentative literature positioning section for high-impact academic journals. It teaches researchers how to move beyond simple citation lists by systematically confronting the nearest competing works, clearly defining the unique marginal contribution, and establishing the necessary context ("why now?") for the research, ensuring the work's novelty and readability.

This skill guides authors on how to proactively strengthen their academic manuscripts before submission, especially for highly demanding journals. It involves identifying the most likely expert reviewers, predicting their specific methodological, theoretical, or empirical objections, and strategically integrating countermeasures, robustness checks, and alternative explanations directly into the main text. It transforms the submission process from a defensive reaction to a proactive, structured argument.

This guide details how to assemble a submission-ready replication package for top academic journals, such as The Review of Economic Studies (REStud). It covers the necessary repository structure, mandatory README sections, and coding best practices (e.g., master scripts, relative paths, version pinning) to ensure that the data and code can be fully reproduced and verified by journal editors before publication.