Skill UI

This skill provides a comprehensive guide for authors targeting the high-level academic journal, *Finance and Trade Economics*. It helps users assess if their manuscript's scope, methodology, and core contribution align with the journal's specific focus areas (e.g., fiscal policy, budget governance, international trade). It outlines strict submission formats, common rejection pitfalls, and alternative journal suggestions, ensuring academic rigor and proper positioning.

This guide outlines the rigorous methodological standards required for empirical finance manuscripts. It covers essential details from sample construction (attrition tables, survivorship bias) to variable definition, merge integrity, and appropriate statistical inference (clustering, panel structure). Use this to harden your data layer and ensure your methodology is robust enough to pass peer review in top finance journals.

This guide outlines advanced econometric strategies and best practices for establishing causal identification in corporate finance and asset pricing. It addresses common methodological pitfalls, such as endogeneity, spurious correlation, and weak designs, providing specific techniques (e.g., staggered DiD, robust IV inference) required to defend a research paper's claims to top-tier academic journals.

This guide instructs authors on crafting highly targeted and convincing robustness sections for empirical finance papers. Instead of merely adding volume, it teaches the concept of 'subtraction, then precision'—identifying specific alternative explanations (threats) a referee might raise (e.g., reverse causality, omitted variables) and selecting the minimal, most effective check to neutralize each threat. This aligns with the philosophy of top-tier financial journals that value new ideas over superficial testing.

This guide helps researchers assess the scope and fit of their international macro-finance topics for the IMF Economic Review (IMFER). It emphasizes the necessity of linking rigorous academic findings to explicit, global policy relevance, especially concerning open economies, capital flows, and global spillovers.

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 provides a structured framework for building and auditing empirical data and estimation pipelines in finance and banking research. It covers data construction from various sources (e.g., CRSP, Call Reports), advanced econometric techniques like fixed effects and winsorization, conducting stress tests (e.g., crisis periods, large banks), and ensuring full reproducibility. It emphasizes reporting results with meaningful economic magnitudes.

A comprehensive guide for stress-testing and defending empirical identification strategies in finance and economics manuscripts. It covers advanced econometric techniques such as Staggered DiD, Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Event Studies, providing actionable advice on fixed effects, clustering, necessary robustness checks, and anticipating referee challenges.

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.

This guide provides comprehensive guidelines for preparing high-quality, publication-ready tables and figures specifically tailored for Journal of Banking & Finance (JBF) submissions. It covers everything from structuring descriptive statistics and regression results to designing event-study plots and ensuring proper notes and execution workflows.

A comprehensive guide for conducting advanced empirical analysis required for top-tier finance journals. It covers assembling multi-source firm panels (Compustat, CRSP, etc.), constructing complex corporate finance variables, implementing advanced econometric techniques (high-dimensional fixed effects, clustered errors), and systematically planning robustness checks and replication strategies.

A comprehensive guide for designing and defending the causal identification strategy in empirical corporate finance research. It covers advanced methods such as Staggered DID, Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Event Studies, providing checklists to address crucial econometric threats like endogeneity, selection bias, and reverse causality for high-impact publications.