Skill UI

This comprehensive guide outlines the rigorous methodology required for empirical and theoretical growth studies, particularly for high-impact journals like JEG. It covers best practices for cross-country panel data analysis, calibration techniques, spatial inference (Conley SEs), and structuring robust manuscripts. Use this checklist when estimating growth outcomes, simulating transition paths, or conducting deep sensitivity analyses for development economics.

A comprehensive guide for preparing high-quality tables and figures, specifically tailored for submissions to the Journal of Economic Growth (JEG). It dictates the necessary narrative flow—from identifying empirical facts to detailing mechanisms, model estimates, and robustness checks. The guide covers best practices for map generation, handling cross-country panels, and ensuring that all exhibits collectively tell a clear, coherent story about economic growth and its underlying mechanisms.

This guide provides essential best practices for presenting spatial evidence in academic papers, particularly in economic geography. It emphasizes that maps and tables must make an explicit argument—show variation, spatial discontinuity, or gradients—rather than merely decorating the data. Learn how to properly report spatial model coefficients, handle projections, and avoid common cartographic and statistical pitfalls.

This guide provides best practices for empirical design and microstructure measurement in financial markets. It covers cleaning high-frequency TAQ/order-book data, constructing robust liquidity, spread, and price-impact measures, and meticulously documenting all sample filters and calculation assumptions. Essential for academic research where measurement rigor and transparency are paramount.

This guide provides rigorous best practices for authors presenting empirical evidence in microstructure finance papers. It ensures that tables and figures are self-contained, verifiable, and immediately convey the core mechanism and headline results to a skeptical academic referee, moving beyond simple descriptive statistics.

This guide provides advanced methodological principles for conducting theoretically grounded heterogeneity analysis in financial research. It emphasizes that any dimension used for splitting the data (e.g., ownership, bank type, financial constraint) must be predicted by the underlying economic mechanism, rather than being an arbitrary data exploration. It details best practices, statistical rigor (group coefficient difference testing), and common pitfalls to avoid.

A comprehensive guide on transforming preliminary research findings into publication-quality manuscripts for top-tier finance journals. It covers best practices for slimming over-wide regression tables, generating standardized figures (IRF, Event Study), ensuring continuous numbering, and adhering to strict academic formatting standards.

A comprehensive guide detailing best practices for constructing rigorous and legible tables and figures for health economics manuscripts, particularly for the Journal of Health Economics (JHE). It covers presentation requirements for main policy estimates, identification figures (e.g., event studies, RD plots), and descriptive institutional exhibits, ensuring that the health setting and causal effects are immediately apparent to expert readers.

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.

A comprehensive guide for formatting and creating high-impact tables and figures for academic submissions, particularly adhering to The Journal of Law and Economics (JLE) standards. It teaches how to visually present the main effect of a legal rule (e.g., event-studies, RD, DiD) clearly and concisely, ensuring the core identification is legible at a glance. Covers best practices for standard errors, clustering, and self-contained academic notes.

This guide provides best practices for designing tables and figures for economics manuscripts, specifically following the conventions required by journals like JLEO. It emphasizes foregrounding the institutional or organizational comparison, ensuring exhibits are self-contained, and converting implied arguments (like comparative statics or event studies) into visible, persuasive graphical evidence.

A comprehensive guide to constructing rigorous empirical datasets for academic papers in finance and banking. It covers best practices for handling complex data sources (e.g., bank micro-data, central bank reports, macro series), addressing measurement biases, and ensuring full replicability, adhering to the standards of top-tier economic journals. Focus areas include merger tracking, regime transitions, and variable definition consistency.