Skill UI

A comprehensive guide for submitting high-quality replication packages for academic journals like the American Economic Journal (AEJ: Micro). This package covers two essential components: self-contained, verifiable proofs for theoretical claims (the Proof Appendix), and a fully reproducible code and data deposit (the Code/Data Repository). It ensures that all numerical results, simulations, and empirical findings can be regenerated by the journal's editor, maintaining the highest standards of scientific transparency.

This guide outlines best practices for authors presenting theoretical and empirical results for top-tier journals like the American Economic Journal: Microeconomics (AEJ: Micro). It covers structuring propositions, building transparent numerical examples, creating schematic figures, and formatting tables (including mandated use of standard errors over significance asterisks) to ensure maximum clarity and adherence to academic publishing standards.

This guide helps researchers determine if their microeconomic theory, model, or experiment is suitable for American Economic Journal: Microeconomics (AEJ: Micro). It provides a structured framework for evaluating the contribution's scope, assessing broad microeconomic interest, and differentiating the appropriate venue from competing specialist journals like JET, Econometrica, or AEJ: Applied.

This guide provides stringent methodological standards for establishing credible causal claims in empirical policy manuscripts. It covers advanced econometric techniques—including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Randomized Controlled Trials (RCT)—required to move beyond mere correlation and prove that the observed effect is genuinely caused by the policy intervention.

This guide outlines how to elevate a research paper beyond merely presenting new estimates. It teaches authors to frame their contributions around actionable policy gaps, welfare improvements, and cost-benefit analyses, ensuring the 'so what' for policymakers is the primary takeaway. Essential for academic writing in economics.

This guide outlines how to structure a rigorous robustness program for economic policy manuscripts. It emphasizes defending the overall policy takeaway, rather than merely reporting coefficient significance. Users learn to address common econometric threats—such as specification changes, pre-trends, multiple testing, and selection on unobservables—using advanced techniques (e.g., Wild-cluster bootstrap, Oster bounds) to ensure the policy conclusion is stable and credible.

This guide details best practices for transforming raw econometric outputs (coefficients, significance stars) into self-contained, policy-message-carrying exhibits for top-tier economic journals (e.g., AEJ: Policy). It emphasizes replacing significance stars with standard errors (SEs) or confidence intervals (CIs), creating a 'headline exhibit' that communicates the policy effect in interpretable units, and structuring tables and figures for maximum clarity for non-academic policymakers.

This skill acts as a central workflow router for manuscripts targeting the American Economic Journal: Economic Policy (AEJ: Policy). It diagnoses the current stage of a paper—whether it's topic selection, design, modeling, writing, or rebuttal—and recommends the next specialized skill. It ensures the research maintains a strong focus on credible causal evidence and actionable policy implications.

A comprehensive guide for drafting and revising economic policy manuscripts, particularly the abstract and introduction. It teaches authors how to convert complex causal estimates into clear, actionable policy takeaways while adhering to rigorous academic house style, ensuring claims are calibrated and non-overstated.

This guide provides rigorous methodological guidelines for ensuring the identification strategy in high-impact empirical economics papers (AER: Insights). It covers key areas including Difference-in-Differences (DiD), Regression Discontinuity Design (RDD), Instrumental Variables (IV), and structural parameter identification. It emphasizes the need for extreme methodological clarity, transparency, and conciseness required for top-tier academic publication.

This skill guides researchers on how to triage numerous robustness checks for short-format academic manuscripts (e.g., AER: Insights) constrained by word and exhibit limits. It teaches the 'minimum credible set' approach: identifying the 1-2 core checks that defend the central hypothesis for the main text, while systematically moving all supplementary checks to the Appendix and properly signposting them in one sentence to maintain credibility.

This skill guides authors on condensing complex empirical research findings (tables and figures) to meet the strict formatting constraints of top academic journals like AER: Insights. It enforces a maximum of five one-page exhibits, teaches authors how to select the headline result, central diagnostics, and mechanism, and ensures adherence to specific house styles, such as reporting standard errors instead of significance asterisks, while managing word count budgets.