Skill UI

This tool helps researchers diagnose whether their empirical or theoretical result meets the high standards required for top-tier academic journals like Econometrica. It guides users to evaluate the generality, methodological novelty, and theoretical depth of their work, ensuring the contribution is a generalizable estimator or theorem, not merely an application.

This guide offers a rigorous framework for structuring advanced econometric theory papers. It details how to move beyond simple identification by defining minimal, defensible assumptions, proving advanced limit theorems (e.g., FCLT, high-dimensional limits), and ensuring the result's generality across various data regimes (stationary, nonstationary, semiparametric). Use this when theoretical rigor is the primary challenge.

This skill guides researchers on how to position a new econometric theorem by rigorously comparing it against the existing theoretical literature frontier. Instead of a general survey, it requires defining the 'delta'—the specific element (e.g., weaker assumptions, broader scope, generalization) that distinguishes the new result from prior work, using formal APA author-date citations. Essential for high-level academic manuscripts.

This guide helps researchers determine if their econometric result is a general, foundational theory contribution (such as asymptotics or proofs) or merely an applied estimate. It provides a framework for assessing theoretical rigor, identifying generalizations, and deciding whether the work fits a full Article or a concise Miscellanea, ensuring proper submission targeting for top-tier journals.

This guide provides strict guidelines for authors submitting econometrics papers, detailing how to strategically compress, optimize, and structure academic exhibits (tables, figures, simulations). It ensures that critical results and diagnostic information are presented clearly within tight page constraints, maximizing impact while adhering to journal standards.

This guide outlines the mandatory structure for creating a reproducible research package, required by academic journals like the European Economic Review (EER). It details how to properly assemble raw data, master analysis scripts, environmental specifications, and comprehensive documentation (README) to ensure that reported results can be independently verified by others. It is essential for any paper involving empirical analysis or simulations.

A comprehensive guide for building a 'robustness battery' to validate empirical findings. It instructs researchers on thoroughly testing results against potential weaknesses in specification, sample selection, measurement, estimator choice, and inference assumptions. Essential for publishing rigorous, credible quantitative research.

A comprehensive guide for authors preparing manuscripts for top economics journals (e.g., EER). It details best practices for designing self-contained tables and figures, emphasizing the correct reporting of standard errors (SEs), confidence intervals (CIs), and interpreting results cleanly. This guide ensures exhibits adhere to rigorous academic publishing standards, moving beyond simple star counts to let the magnitude of the result speak for itself.

This guide provides detailed reporting norms for reducing and analyzing complex Earth and Planetary Science Letters (EPSL) data, specifically focusing on isotope geochemistry and geochronology. It mandates full uncertainty budgeting, proper statistical interpretation (e.g., MSWD, weighted means), and thorough model diagnostics to ensure results are scientifically defensible and reproducible.

This guide details the best practices for creating high-impact exhibits for scholarly manuscripts, particularly in Entrepreneurship Theory and Practice (ETP). It covers structuring empirical results (using magnitude over significance stars), developing vital theoretical mechanism figures, and presenting qualitative data using structures like the Gioia model, all adhering to APA standards.

A comprehensive guide on designing self-contained, high-impact tables and figures (Exhibits) for quantitative sociological manuscripts, specifically adhering to European Sociological Review (ESR) standards. It covers best practices for presenting cross-national, longitudinal, and comparative data, emphasizing magnitude, uncertainty (e.g., forest/caterpillar plots), and strict reproducibility to ensure results stand alone for double-blind review.

This guide provides rigorous guidelines for designing and presenting results in Experimental Economics manuscripts. It emphasizes making the treatment comparison and its uncertainty immediately visible through specific figure types (distributions, dynamics plots) and structured tables, ensuring the findings are self-contained and highly credible for academic review.