Skill UI

This guide helps authors polish the prose, abstract, and introduction of quantitative economics manuscripts for a general-interest Econometric Society readership. It emphasizes structuring the paper to clearly present both a substantive economic question and a quantitative method. It adheres to QE house rules, requiring findings to be communicated through point estimates with standard errors and confidence sets, rather than relying on statistical asterisks.

This comprehensive guide details advanced econometric methodologies required for rigorous causal inference studies. It covers how to defend both the causal identification strategy (DiD, RD, IV) and the quality of variables (handling measurement error, index construction). Learn to meet the stringent standards of top-tier journals by applying techniques like staggered DiD estimators, density testing, and attenuation correction.

This guide details the best practices for structuring supplementary materials for scientific conferences, ensuring the main paper remains self-contained. It covers transforming raw data, failure logs, and robotic videos into credible evidence annexes. Key areas include anonymization of media, maintaining archive hygiene, and structuring appendices to deepen belief without being mandatory for understanding the core claims.

Provides comprehensive guidelines for designing and auditing academic tables and figures, specifically for development economics journals. It teaches how to translate statistical coefficients into actionable policy magnitudes, validate research design (e.g., balance checks, pre-trends), and adhere to strict page limits while maintaining clarity for both economists and policymakers.

A comprehensive guide for preparing replication and transparency packages for World Development manuscripts. It provides checklists and best practices for both quantitative (code reproducibility, data provenance, de-identification) and qualitative (evidence-to-claim trail, methods appendix) research. It addresses ethical constraints and the unique challenges of double-anonymized review.

Matplotlib is the foundational Python library for creating static, animated, and high-quality visualizations. This comprehensive skill guide covers everything from basic line plots and scatter graphs to advanced concepts like multi-subplot layouts, heatmaps, and 3D visualization. It details both the convenient pyplot interface and the powerful object-oriented API, ensuring you can generate publication-ready charts with professional customization.

This skill parses standardized C-CDA/CCD XML clinical documents exported from EHRs. It extracts both human-readable section narrative text and coded entries, mapping them by LOINC codes and template IDs. It is essential for preparing clinical free-text data for subsequent NLP analysis and supports XML-aware de-identification while preserving document structure.