Skill UI

A comprehensive guide for authors submitting to international finance journals, detailing how to structure the online supplementary appendix and prepare the data-and-code deposit. It ensures that supporting material is organized, traceable to main claims, and that data accessibility statements are compliant with institutional policies, especially for restricted international data.

A comprehensive guide and package structure for preparing empirical law and economics manuscripts for journal submission, ensuring full data and code reproducibility prior to publication. It mandates the assembly of data files, transformation scripts, a master execution script, and detailed README documentation, explicitly addressing the unique challenges of restricted or proprietary legal data sources (e.g., sealed court records).

A comprehensive checklist for authors submitting manuscripts to The Journal of Law and Economics (JLE). It guides users through critical pre-submission steps, including single-blind formatting, confirming the required US$100 fee, adhering to Chicago author-date style, and ensuring data replication readiness. Use this guide for the final review before pressing submit.

This guide details how to assemble a comprehensive, reproducible replication package for academic manuscripts, especially in fields relying on complex institutional data (e.g., court records, contracts). It mandates creating a one-command master script, documenting the entire data pipeline from raw sources to final exhibits, and providing detailed protocols for hand-coded variables and data provenance. The goal is to ensure that any researcher can perfectly reproduce every finding.

A comprehensive checklist designed for authors preparing a manuscript for submission to the Journal of Law, Economics, and Organization (JLEO). This guide ensures adherence to Oxford University Press (OUP) standards, covering formatting, anonymization rules, conflict of interest disclosures, data availability statements, and replication package readiness before uploading to the Editorial Express portal.

A comprehensive guide for conducting and reporting rigorous statistical analysis for academic marketing manuscripts, particularly tailored for the Journal of Marketing (JM) standards. It covers selecting appropriate estimators for various designs (e.g., panel, choice, field experiments), managing identification, testing robustness, and adhering to the mandatory reporting of p-values, standard errors, and managerial effect sizes. Also covers data replication and advanced econometric techniques.

A comprehensive guide for authors submitting empirical or quantitative manuscripts to the Journal of Monetary Economics (JME). It details mandatory requirements for data deposition, model code (Dynare, MATLAB, Stata, R), master scripting, and adherence to Elsevier's generative AI declaration, ensuring maximum reproducibility and meeting high academic standards.

A comprehensive guide detailing the data sharing and transparency requirements for submitting manuscripts to the Journal of Marriage and Family (JMF). It specifically addresses the challenge of restricted-use family datasets, teaching researchers how to document access paths and ensure replication-level detail without direct data redistribution.

This guide assists researchers in aligning their study design—whether behavioral (lab/field experiments) or modeling-econometric (IV/DiD/RDD)—with the rigorous standards required by the Journal of Marketing Research (JMR). It covers best practices for causal identification, power analysis, structural estimation, and meeting journal-level expectations like replication and Web Appendix planning.

A comprehensive guide for authors managing a Revise-and-Resubmit (R&R) from the Journal of Marketing Research (JMR). It outlines how to systematically address dual concerns—research rigor (statistics, identification, replication) and theoretical substance (contribution)—while crafting a point-by-point response letter. It emphasizes using the Web Appendix to manage new analyses without exceeding the page limit.

Provides comprehensive guidelines for authors submitting to the Journal of Econometrics (JoE). It details the required best practices for data citation (using the Elsevier `[dataset]` format), ensuring methodological reproducibility (e.g., Monte Carlo simulations), and preparing estimators as runnable code packages (R, Python, etc.). This guide is essential for meeting rigorous academic publication standards and passing peer review.

This comprehensive guide outlines the mandatory standards for data and code submission for academic papers published in the Journal of Labor Economics (JOLE). It instructs researchers on how to build a complete, reproducible package, detailing the requirements for documenting the full data chain (raw to final), master scripts, environment pinning, and handling proprietary data for journal review.