Skill UI

A comprehensive guide for structuring point-by-point responses to reviewers after a major academic review (RED). It emphasizes prioritizing model critiques, quantitative evidence, calibration discipline, and maintaining code/data archive updates. This skill ensures your rebuttal is structured, rigorous, and directly addresses the core concerns of quantitative reviewers.

Provides a comprehensive guide to the Review of Economic Dynamics (RED) editorial process, detailing the suitability screen, single-anonymized refereeing model, and fast-review expectations. It guides authors on preparation, planning timelines, and common pitfalls to ensure a smooth submission experience.

This guide outlines best practices for creating quantitative exhibits in dynamic macroeconomics papers. It covers crucial components like Impulse-Response Functions (IRFs), calibration tables, moment-matching results, and policy counterfactuals. The focus is on ensuring the model's mechanism and quantitative fit are clear, legible, and self-contained for expert review.

Guides authors through the rigorous, end-to-end lifecycle of submitting a paper to the Review of Economic Dynamics (RED). It acts as an orchestration checklist, covering critical stages from initial scope definition and quantitative modeling to data archiving, manuscript formatting, fee payment, and handling revisions. It ensures authors maintain methodological rigor and code-first discipline throughout the entire academic publishing process.

This skill guides the execution and stress-testing of empirical analysis for innovation studies (Research Policy). It details how to build reproducible bibliometric and patent variables, select appropriate econometric models (like Poisson/Negative Binomial for counts), and establish robust evidence. The focus is on addressing methodological challenges, ensuring transparent variable construction, and performing rigorous sensitivity checks to withstand expert scrutiny.

A methodological guide for empirical economists on balancing theoretical depth with empirical findings. It advises authors on how to structure models—determining if a structural, light, or minimal theory dose is appropriate—to ensure the core contribution remains the testable estimate, rather than the theory itself.

This guide provides a rigorous framework for stress-testing and implementing state-of-the-art causal identification strategies required for high-impact empirical economics. It covers advanced methodologies including Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity (RDD), Synthetic Control, and Structural Modeling. It emphasizes modern estimators (e.g., Callaway-Sant'Anna, effective F) and robust diagnostic checks to ensure the causal claims are methodologically sound and defensible.

This guide provides rigorous best practices for developing and presenting theoretical economic models for top-tier journals. It emphasizes framing results with a clear economic payoff, maintaining minimal model setups, and ensuring that complex, full proofs are relegated to the online appendix. The goal is to ensure the primary economic insight remains highly visible and actionable, rather than being buried in algebraic machinery.

A comprehensive guide for tackling a 'revise-and-resubmit' academic review (R&R). This process details how to substantively resolve critical, first-order concerns—such as identification threats, construct measurement, or model assumptions—before drafting the letter. It emphasizes rigorous analysis, structured point-by-point responses, maintaining manuscript consistency, and preserving anonymity for resubmission.

This skill is a comprehensive fit and re-framing tool for quantitative macroeconomists targeting top-tier dynamic economics journals like the Review of Economic Dynamics (RED). It provides a detailed checklist covering structural model requirements, data discipline (calibration/estimation), computational rigor, and adherence to specific house styles, helping authors assess their manuscript's suitability before submission.

A comprehensive guide for authors addressing the rigorous identification requirements for industrial-organization (IO) manuscripts, particularly targeting top-tier journals like the RJE. It details structural and reduced-form modeling approaches for areas including demand, supply, entry, mergers, and auctions. The resource emphasizes defending endogeneity, selecting appropriate market-based instruments, utilizing modern econometric estimators (e.g., Callaway–Sant'Anna), and establishing clear causal links between variation and structural parameters.

Comprehensive guidelines for auditing and reproducing high-stakes empirical financial research. This resource details the rigorous standards required for top-tier finance journals, covering sample construction, identifying variables, advanced econometric modeling (e.g., panel data, factor pricing), handling international cross-market data, and establishing a fully reproducible data pipeline. Essential for ensuring the robustness and credibility of finance findings.