Skill UI

This guide helps authors refine the core contribution sentence for Quantitative Economics (QE) manuscripts. It shifts the focus from complex methodology (machinery) to the clear, quantitative economic answer (the payoff). Learn to structure claims by linking a clear economic question, a measured quantity (estimate, counterfactual), and a broader policy lesson, while explicitly stating scope and uncertainty to meet high academic standards.

A comprehensive guide to ensuring the quantitative rigor and full reproducibility of econometrics manuscripts, particularly for submissions to high-tier journals like QE. Covers structural estimation (GMM, MSM), moment construction, data cleaning best practices, and comprehensive validation checks (e.g., multi-start, Monte Carlo recovery). It ensures that all results can be regenerated from raw data using pinned environments and documented scripts.

Provides detailed guidelines for constructing high-quality tables and figures for Quantitative Economics (QE) manuscripts. It emphasizes adhering to strict academic standards, such as replacing significance asterisks with standard errors and confidence bands, placing exhibits in-text, and ensuring all visuals are self-contained, professionally formatted, and journal-compliant.

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.

Mandatory package structure for submitting accepted empirical papers to the Quarterly Journal of Economics (QJE). It ensures complete research reproducibility by organizing raw data, derived files, and analysis code. This package guides authors in creating a comprehensive, self-contained deposit that allows any investigator to regenerate every figure, table, and result published in the manuscript, adhering to strict academic data-availability policies.

A comprehensive methodological guide for structuring the robustness checks and online appendix of high-level empirical economics manuscripts, specifically tailored to the standards of the Quarterly Journal of Economics (QJE). It provides a structured approach to defending the identification assumption, selection, measurement, and inference, ensuring the paper anticipates and addresses potential referee critiques.

This skill helps authors assess the suitability of their structural, computational, or econometric manuscript for top-tier quantitative economics journals. It guides authors on meeting the high bar for model rigor, identification transparency, and computational evidence required for publication in this field, acting as a comprehensive fit and re-framing tool.

This tool guides authors writing on industrial organization, market structure, regulation, and antitrust. It provides a rigorous framework for evaluating whether a manuscript meets the high standards of top-tier IO journals by assessing theoretical models, empirical identification, and policy significance. Use it for venue selection and manuscript re-framing.

This skill guides researchers on how to assess the suitability of their manuscript for the journal Research on Economics and Management. It provides detailed information on the journal's scope, required theoretical depth, methodological rigor (e.g., internal validity, identification strategies), structural expectations, and common pitfalls to avoid, ensuring submissions are properly framed and targeted.

This guide provides best practices for building self-explanatory, high-impact exhibits for interdisciplinary academic manuscripts. It covers the structured design of complex visualizations, including regression tables, bibliometric maps, event-study plots, and qualitative data structures. The goal is to ensure every figure and table carries the core innovation mechanism and is immediately interpretable by diverse readers (e.g., policymakers, managers, and economists).

This strategy guides researchers in anticipating the specific, rigorous methodological objections raised by top-tier academic referees, especially in applied econometrics. It provides a systematic map connecting econometric designs (like DID, IV, RD) to common threats (e.g., measurement error, bias, specification issues). Users can pre-empt these criticisms by structuring their manuscript to include necessary defenses, robustness checks, and scope limitations before formal submission.

This guide outlines the comprehensive policy and architecture required for submitting a fully reproducible replication package to The Review of Economics and Statistics (REStat). It details how to structure the repository, including data, master scripts, and the README file, ensuring that every result can be traced and regenerated by other researchers.