Skill UI

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.

A comprehensive guide for authors writing empirical papers (especially in finance/economics). It teaches the critical skill of separating load-bearing claims (must be in the main text) from exhaustive supporting evidence (best placed in the Internet Appendix). It details how to build a fully reproducible package, including data lineage, codebooks, and documenting proprietary data access paths.

This comprehensive guide assists in executing and documenting rigorous empirical finance research, tailored for top-tier journals like JFQA. It covers the entire pipeline, including complex financial data construction (CRSP, Compustat), advanced data cleaning (winsorizing, outlier handling), and sophisticated econometrics (fixed effects, clustered standard errors, Fama-MacBeth). The core focus is achieving absolute reproducibility, ensuring that all filters, robustness checks, and analytical steps are meticulously documented for archival and peer review.

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).

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 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 skill guides authors on positioning and framing manuscripts for the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING). It provides detailed advice on core fit, required evidence (e.g., documentation, licensing, annotation reliability), and rhetorical structure needed to ensure a paper resonates with the specialized audience of language resources and computational linguistics.

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.

This skill guides authors on meeting stringent academic requirements for manuscript submission, specifically addressing the mandatory replicability standard set by The Journal of Politics (JOP). Acceptance is strictly contingent on providing a complete, documented, and executable package. The required materials include the dataset(s), master code, codebook, and a comprehensive readme file, ensuring that any published finding can be independently verified and reproduced by a journal analyst. It also provides guidelines for handling restricted data.

A comprehensive guide for authors submitting policy evaluation manuscripts to academic journals. It outlines the rigorous standards required to ensure full research reproducibility, detailing the process of archiving data and code in public repositories, creating master scripts, and providing documentation for restricted administrative data access.

This guide helps authors prepare manuscripts for high-impact journals, specifically detailing the mandatory requirements for data and code transparency (e.g., JPART). It outlines how to build a complete, reproducible package, including master scripts, documentation (README), data availability statements, and managing potential data restrictions, ensuring publication acceptance is not stalled by materials.

A comprehensive preflight checklist for submitting academic manuscripts to the Journal of Urban Economics (JUE) via Elsevier Editorial Manager. It guides authors on mandatory formatting standards, required documentation (e.g., standard errors, exhibits), submission fees, and critical strategic elements like the confidential data exemption and structuring the cover letter. Use this before final submission to ensure compliance and maximize acceptance chances.