Skill UI

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.

A comprehensive guide for empirical finance researchers on structuring robustness checks and handling multiple testing concerns for top-tier journals like The Journal of Finance. It teaches how to distinguish load-bearing checks for the main text versus exhaustive analyses relegated to the Internet Appendix, ensuring methodological rigor and maximizing impact.

This guide outlines the rigorous standards for presenting tables and figures in manuscripts submitted to The Journal of Finance (JF). It emphasizes the need for self-contained, accessible exhibits, ensuring that readers from any subfield can interpret the results solely from the caption and notes. Key standards include using economic units (bps, % of market cap), proper numbering schemes (Roman/Arabic), and separating decisive findings from exhaustive details in the Internet Appendix.

A comprehensive methodological guide for conducting rigorous quantitative research in finance, covering asset pricing, corporate finance, and econometrics. This skill defines the necessary standards for factor construction, portfolio sorting, advanced estimators (Fama-MacBeth, GMM), robust standard error clustering, and multiple-testing discipline. It ensures research designs are academically sound, reproducible, and suitable for top-tier financial journals.

A comprehensive guide for handling endogeneity, selection bias, and causal inference in empirical finance research, particularly targeting the high standards of journals like JFE. It details advanced econometric methodologies including Difference-in-Differences (DID), Regression Discontinuity Design (RDD), and Instrumental Variables (IV), ensuring your causal claims are rigorously defensible against referee scrutiny.

Provides a comprehensive framework for constructing a robust battery of empirical tests, tailored for high-impact academic journals like JFE. This guide covers alternative measures, specifications, subsamples, and falsification tests, ensuring research findings are highly credible and capable of withstanding rigorous academic scrutiny.