Skill UI

Provides comprehensive guidelines for authors submitting empirical, quantitative, or theoretical growth papers. It details how to package data sources, code pipelines, calibration files, and historical/geospatial artifacts to meet stringent reproducibility standards for publishing journals.

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 comprehensive guide provides advanced methodological strategies for authors submitting to the Journal of Economic Geography (JEG). It addresses critical challenges in establishing causal inference using spatial data, such as spatial autocorrelation, spillover effects (SUTVA violations), and structural elasticity identification. It covers modern techniques for spatial DID, Network Equilibrium Models (NEG), and qualitative case studies, ensuring methodological rigor.

A comprehensive guide for authors in spatial economics on conducting rigorous robustness checks. It systematically addresses common spatial threats—such as the Modifiable Areal Unit Problem (MAUP), spatial weight matrix sensitivity, and spatial autocorrelation—to ensure published results are scientifically sound and not artifacts of the data definition or model specification. Essential for high-level academic submissions.

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.

A comprehensive guide for authors publishing in economic geography journals, detailing how to structure manuscripts to satisfy both economic and geographical communities. It provides methodological advice on transitioning between formal NEG/quantitative-spatial models and conceptual/evolutionary frameworks, ensuring that the underlying mechanisms and assumptions are transparent and testable.

A comprehensive guide for calibrating the balance between coverage and emphasis when conducting literature surveys (JEL surveys). It provides guidelines for structuring the corpus by tiers, ensuring fair representation of all academic schools and controversies, and avoiding self-promotion bias.

This guide outlines a systematic methodology for gathering, reading, and synthesizing large bodies of academic research for comprehensive economic surveys (JEL style). It moves beyond simple summarization by enforcing structured data collection into a detailed evidence matrix. The process ensures maximum coverage through advanced search techniques (e.g., snowballing, JEL code sweeps) and focuses on synthesizing connections, identifying consensus, and articulating scholarly tensions across different studies.

This tool provides a comprehensive pre-submission checklist designed for authors submitting survey papers (either a proposal or a full draft) to the Journal of Economic Literature (JEL) via the AEA portal. It ensures compliance by verifying JEL codes, disclosure statements, data availability, and adherence to style guides, helping authors finalize their submission package.

A comprehensive guide for designing and stress-testing asset-pricing empirical models, tailored for submissions to top-tier finance journals. Covers methodologies like Fama–MacBeth regressions, factor model comparisons, handling standard-error subtleties, and rigorous out-of-sample validation. Essential for ensuring results survive academic scrutiny, addressing issues like multiple testing and economic magnitude.

A comprehensive guide for strengthening causal claims in corporate and empirical finance research. This resource details advanced econometric methods—including IV, DiD, RDD, and natural experiments—and provides strategies to preempt common methodological attacks (e.g., endogeneity, parallel-trends violations) required by top-tier academic journals like the Journal of Finance.

A comprehensive guide for structuring responses to highly selective academic journal reviews, specifically for The Journal of Finance (JF) revise-and-resubmit manuscripts. It details how to prioritize the editor's central concerns over individual referee points, manage the revision process, utilize the Internet Appendix, and adhere to strict journal formatting and code-sharing guidelines.