Skill UI

This comprehensive skill is a guide for authors to assess if their Information Systems (IS) manuscript is suitable for the prestigious Information Systems Research (ISR) journal. It analyzes the journal's rigorous requirements, including the need for genuine IS theoretical contributions, quantitative methodology (econometrics, analytical modeling), and adherence to specific submission standards. It functions as a pre-submission checklist and re-framing tool, helping authors understand the required depth in theory, evidence, and structure before targeting the venue.

A comprehensive guide for conducting empirical data analysis in International Relations (IR). This skill addresses specific econometric challenges inherent to IR data, such as dyadic dependence, state selection bias, and gravity modeling. It guides users through rigorous reporting standards, advanced statistical methods, and verification-readiness protocols required by top-tier academic journals.

This guide outlines the mandatory data and code requirements for publishing manuscripts in International Organizations (IOs). It details the rigorous process—from conditional acceptance to final publication—which requires authors to prepare complete, reproducible packages. Key steps include submitting data/code, undergoing external re-running of quantitative results, verifying formal model proofs, and depositing materials with a DOI in the IO Dataverse.

A comprehensive guide for authors handling a journal's revise-and-resubmit (R&R) decision. It outlines the critical sequence: prioritizing new analyses (identification, channel, measurement) over writing, triaging referee concerns (first-order vs. second-order), drafting evidence-backed responses, and updating the complete data-and-code package. Essential for quantitative researchers aiming for publication.

A comprehensive guide for advanced quantitative research, focusing on demonstrating the validity of econometric methods. It outlines best practices for combining rigorous Monte Carlo simulations (stress-testing DGPs, baselines) with substantive real-world data applications, essential for publication in high-impact economics and statistics journals.

A comprehensive guide for structuring quantitative exhibits for scholarly manuscripts, specifically tailored for educational psychology journals. It focuses on adhering to APA 7th edition standards, accurately presenting model-based results, effect sizes with confidence intervals (CIs), growth trajectories, and ensuring full anonymization for masked review. It teaches researchers how to make complex statistical arguments legible and reproducible.

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 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 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 to designing highly defensible and causal research studies for top-tier finance journals, such as the Journal of Financial and Quantitative Analysis (JFQA). It covers advanced econometric methods for corporate finance, asset pricing, and policy shocks, including Fixed Effects, Staggered Difference-in-Differences (DID), Instrumental Variables (IV), and Regression Discontinuity Design (RDD). Focuses on addressing endogeneity, reporting economic magnitude, and ensuring robust inference.

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 serves as a preflight checklist for authors submitting manuscripts to the Journal of Financial and Quantitative Analysis (JFQA). It details stringent requirements, including double-anonymous formatting, specific layout standards (8.5x11, 12pt Times New Roman, double-spaced), the 100-word abstract limit, and mandatory disclosure rules regarding prior rejections and code-sharing. Use this checklist before submitting via Editorial Manager to ensure compliance and avoid desk rejection.