Skill UI

This guide helps researchers strategically assess whether their empirical microeconomics project is best suited for the American Economic Journal: Applied Economics (AEJ: Applied). It provides a structured framework to test the project's causal design, scope, and cross-field appeal, ensuring the question is 'AEJ: Applied-shaped' rather than being too general (AER) or too specialized (Field Journal).

This guide outlines the rigorous methodological standards for empirical identification in macroeconomics, crucial for submitting to top-tier journals. It covers advanced techniques such as Structural VAR (SVAR), Local Projections (LP), and handling high-frequency/micro-data shocks. It ensures authors explicitly defend the mapping from raw data to dynamic causal objects, addressing critical issues like endogeneity, anticipation, and structural breaks, and providing execution checklists for modern econometric tools (DiD, IV, RDD).

This guide provides a structured methodology for articulating the unique and marginal contribution of a scholarly paper, particularly within macroeconomics. It teaches authors how to bridge the gap between theoretical modeling (quantitative-theory) and data-driven evidence (identified-empirical), ensuring that the novelty and scope are clearly communicated to a broad, general expert audience.

A comprehensive guide for authors responding to major journal decisions (e.g., R&R or reject-with-comments) in economics. This skill teaches a systematic approach to triaging reviewer comments, structuring the rebuttal letter point-by-point, and ensuring revisions are supported by new empirical evidence rather than just prose. It focuses on maintaining academic rigor and professional communication.

A comprehensive framework designed to rigorously test the stability of key macroeconomic findings. This program addresses potential biases arising from specification choices, sample periods (e.g., Great Moderation, ZLB, COVID breaks), and methodological variations (SVAR vs. LP). It ensures that the reported headline quantity remains robust even when challenged by a skeptical academic referee, providing a targeted defense rather than simply listing extra tables. Ideal for high-stakes empirical macro papers.

This skill acts as a comprehensive workflow router for manuscripts targeting the American Economic Journal: Macroeconomics (AEJ: Macro). It guides the researcher through the entire publication lifecycle—from initial topic selection and literature positioning, through rigorous quantitative modeling (DSGE, SVAR), empirical identification, writing, to final submission and rebuttal strategy. It ensures the final paper meets the high standards of modern macroeconomics research.

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 skill acts as a workflow router, guiding researchers through the entire manuscript lifecycle for submissions to American Economic Journal: Microeconomics (AEJ: Micro). It does not write the paper, but diagnoses the current bottleneck—whether it's topic selection, model refinement, empirical testing, or rebuttal strategy—and specifies which specialized aejmic-* sub-skill to invoke next, ensuring the paper aligns with the specific requirements of AEJ: Micro. Triggered when users are unsure what step to take next, or when revising based on reviewer comments.

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.

A comprehensive framework for translating reduced-form causal estimates (e.g., elasticity, treatment effects) into explicit policy statements. It guides researchers on building clear welfare, cost-benefit, or optimal-policy models, defining sufficient statistics, and articulating distributional effects, ensuring policy claims are rigorously grounded in empirical data.

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.