Skill UI

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 guide teaches how to restructure complex econometric tables and figures for manuscripts intended for a dual audience of professional economists and non-technical policymakers. The focus is on clarity, interpretability, and impact, ensuring that the main text presents policy-relevant findings (e.g., event studies, welfare decomposition) while relegating dense technical details (full regression dumps, diagnostics) to the appendix. It emphasizes translating standard coefficients into meaningful units like jobs or % of GDP.

This guide outlines rigorous standards for incorporating theoretical and quantitative models into economic policy manuscripts. It emphasizes that models must be minimal, transparent, and directly bear policy weight—converting estimates into statements about welfare, fiscal costs, or clear mechanisms. It teaches how to design models that pass 'the necessity test,' ensuring policymakers can trace headline numbers directly back to key, identifiable assumptions.

This comprehensive guide provides best practices for designing, running, and reporting computational experiments for academic journals. It teaches authors how to make performance claims scientifically defensible by addressing potential referee criticisms (e.g., tuning artifacts, seed luck). It covers advanced statistical techniques (performance profiles, nonparametric tests) and details the full structure required for a complete, verifiable GitHub data deposit.

A comprehensive guide for preparing high-impact tables and figures for IMF Economic Review (IMFER) manuscripts. It dictates best practices for communicating international macro results to a dual audience of econometric referees and policy makers. Key principles include transparent country coverage, replacing significance asterisks with confidence intervals, and expressing coefficients in policy-relevant units (e.g., % of GDP).

A comprehensive guide for structuring quantitative exhibits for scholarly manuscripts, specifically tailored for educational psychology journals. It focuses on adhering to APA 7th edition standards, accurately presenting model-based results, effect sizes with confidence intervals (CIs), growth trajectories, and ensuring full anonymization for masked review. It teaches researchers how to make complex statistical arguments legible and reproducible.

This guide provides essential best practices for presenting spatial evidence in academic papers, particularly in economic geography. It emphasizes that maps and tables must make an explicit argument—show variation, spatial discontinuity, or gradients—rather than merely decorating the data. Learn how to properly report spatial model coefficients, handle projections, and avoid common cartographic and statistical pitfalls.

This guide provides rigorous conventions for constructing self-contained tables and figures for submissions to high-tier finance journals (e.g., JFI). It focuses on structuring exhibits—such as sample construction, event studies, and fixed-effect regressions—to make complex econometric findings accessible and persuasive to banking and intermediation specialists. It guides the visual narrative, ensuring every exhibit is self-sufficient and methodologically transparent.

A comprehensive guide for authors submitting to academic journals, detailing how to structure and build necessary exhibits (tables and figures). It provides distinct guidelines for quantitative work (e.g., SEM results, interaction plots) and qualitative work (e.g., data-structure figures, representative quotes), ensuring all visuals make the argument legible and adhere to strict house style rules.

This guide helps structure the conceptual framework (Theory of Change or Logic Model) for policy research. It moves beyond simple correlation by explicitly mapping the causal chain: identifying the policy lever, the underlying mechanism, and the predicted outcome. It is crucial for establishing external validity and defining scope conditions so that empirical findings can be generalized and actionable by policymakers in different settings.

This guide provides a rigorous framework for evaluating whether a research question is suitable for high-impact policy journals (like JPAM). It trains users to structure ideas by confirming three critical elements: establishing a specific, policy-relevant intervention (the policy), identifying the decision-maker and the counterfactual choice (the decision), and confirming a credible, causal design (exogenous variation). It ensures the research has both empirical rigor and real-world policy stake.

A comprehensive guide for authors responding to 'revise-and-resubmit' decisions in Mathematical Finance journals. It provides a structured approach to triage referee comments regarding proof gaps, assumption scope, novelty, martingale conditions, and financial relevance. Learn how to write a point-by-point response letter and make aligned, rigorous manuscript edits.