Skill UI

This comprehensive guide details how to build a robust, credible, and shareable replication package for a Journal of Economic Geography (JEG) manuscript. It focuses heavily on documenting spatial data provenance, handling version control for boundaries and projections, and scripting complex spatial joins to preempt reproducibility concerns, even though JEG's policy is post-acceptance.

Provides comprehensive guidelines for authors submitting to the Journal of Economic Theory (JET). It details mandatory data sharing (Elsevier Option C), ensuring computational reproducibility for numerical examples, and proper declaration of generative AI usage. This playbook helps authors structure their submissions to meet high academic standards of verifiable evidence and transparency.

A comprehensive preflight guide for authors submitting to the Journal of Economic Theory (JET). It verifies critical technical formatting, reference compliance, ethical disclosures (AI use, data policy), and structural requirements necessary for successful submission via Elsevier Editorial Manager.

This guide assists authors in preparing research materials for submission to the Journal of Financial Intermediation (JFI), adhering to Elsevier Option C. It provides detailed instructions on managing, depositing, citing, and linking research data, code, and algorithms—whether the data is public, proprietary, or restricted (e.g., central bank registers). The goal is to ensure methodological rigor and reproducibility through the Data Statement.

A mandatory guide for authors submitting to the Journal of Financial and Quantitative Analysis (JFQA). This policy dictates the required archive structure, ensuring that all reported findings can be fully reproduced by depositing source code, raw or pseudo datasets, and a detailed execution roadmap in the JFQA Dataverse. It guarantees the highest standards of academic transparency and reproducibility in financial research.

This comprehensive guide outlines the mandatory data and replication policies for submissions to the Journal of Human Resources (JHR). It details best practices for creating robust submission packages, including Data Availability Statements, code packages, and plans for public repository deposit. It ensures maximum reproducibility and adherence to CC0 licensing standards for academic research.

This comprehensive guide details the strict replication and data deposit policies required by the Journal of International Economics (JIE). It ensures that all components—including raw data, cleaning scripts, structural solver code, and master scripts—are properly deposited in a secure repository (like Mendeley Data) before publication acceptance, guaranteeing full research reproducibility.

A comprehensive guide for establishing rigorous causal claims in international macro-finance. This skill addresses complex econometric challenges such as global confounders, policy endogeneity, and high-frequency surprises in open-economy models. It provides methodologies for cross-country panel data, capital control analysis, and advanced inference, ensuring results meet the high standards of top-tier international finance journals.

This guide teaches authors how to precisely position their academic contribution within existing specialized literature, particularly in finance and banking. It moves beyond vague claims by anchoring the work to canonical economic mechanisms and distinguishing the specific 'delta' (new shocks, frictions, or datasets). Mastering this skill ensures the manuscript clearly articulates its unique value and policy relevance to experts.

A comprehensive guide for authors submitting empirical or quantitative manuscripts to the Journal of Monetary Economics (JME). It details mandatory requirements for data deposition, model code (Dynare, MATLAB, Stata, R), master scripting, and adherence to Elsevier's generative AI declaration, ensuring maximum reproducibility and meeting high academic standards.

A comprehensive guide detailing the data sharing and transparency requirements for submitting manuscripts to the Journal of Marriage and Family (JMF). It specifically addresses the challenge of restricted-use family datasets, teaching researchers how to document access paths and ensure replication-level detail without direct data redistribution.

This guide helps researchers determine if their manuscript is suitable for highly quantitative, theory-driven journals. It emphasizes evaluating the core deliverable—whether it consists of a formal model, provable properties, and an algorithm, rather than relying solely on empirical data or policy recommendations. Essential for optimizing journal submission strategy.