Skill UI

This skill is a comprehensive guide for authors to evaluate the suitability of their marketing manuscript for top-tier journals like the Journal of the Academy of Marketing Science (JAMS). It assesses the theoretical grounding, empirical rigor (e.g., SEM, econometrics), market fit, and adherence to academic publishing standards, providing actionable feedback on improving scope and structure before submission.

This skill provides a comprehensive framework for evaluating whether an economics manuscript is suitable for top-tier, general-interest journals like the JEEA. It guides authors on elevating niche findings into broadly relevant contributions, covering general-interest framing, methodological rigor (e.g., modern econometrics), structural house style, and pre-submission checklists for top-5 economics outlets.

This guide provides comprehensive methodology for advanced empirical analysis in Public Economics, particularly for manuscripts using large administrative or register microdata. It covers advanced topics like estimating behavioral elasticities, calculating welfare metrics (MVPF, DWL), and ensuring robust causal identification strategies. It emphasizes translating raw coefficients into policy-relevant quantities with rigorous uncertainty quantification.

This guide establishes rigorous methodological standards for incorporating forecasting and prediction claims in academic manuscripts. It emphasizes the necessity of genuine out-of-sample evaluation, comparison against robust benchmarks (like Random Walk or AR models), and utilizing advanced statistical tests (e.g., Diebold-Mariano) to prove prediction superiority, moving beyond simple in-sample fit reporting.

A detailed guide on establishing and reporting the necessary robustness and sensitivity analyses for manuscripts in quantitative economics and econometrics. It clarifies that the required robustness differs significantly from causal inference studies, emphasizing testing against variations in method choice, parameters, data scope, and sample periods. Provides structured methodologies for generating sensitivity matrices and discussing model stability.

A comprehensive workflow guide designed for submitting manuscripts to The Journal of Quantitative & Technological Economics (JQTE). This router determines the optimal sequence of specialized skills (e.g., topic selection, measurement, econometrics, forecasting, rebuttal) based on the manuscript's current stage or contribution type. It helps researchers structure their work to meet the journal's specific requirements, emphasizing measurable methods and reproducibility over pure narrative causality.

A rigorous methodological framework for identifying core risk and uncertainty parameters in academic research. This guide details how to design experiments or structural models to explicitly separate confounds (e.g., utility curvature vs. probability weighting, preferences vs. beliefs) and ensure that the measured parameter is genuinely identified, thereby enhancing the scientific rigor of behavioral finance and econometrics studies.

A comprehensive guide for assembling a fully transparent and reproducible research package required for academic submissions (e.g., JRU/Springer). It structures the necessary components—including full experimental instructions, source code (z-Tree/Qualtrics), estimation scripts, and de-identified data—to allow any external party to replicate the study's findings end-to-end. Focuses on both procedural reproducibility and structural econometrics re-runnability.

A comprehensive framework for conducting and structuring robustness checks in academic papers, particularly in econometrics and behavioral economics. It guides researchers on identifying specific threats to the core parameter (e.g., functional form dependence, incentive bias, sample selection) and organizing tests by threat, ensuring the findings are statistically reliable and withstand expert scrutiny.

A rigorous guide for advanced spatial econometrics, designed to stress-test causal claims in urban and spatial economics papers. It provides a framework to defend against the three critical spatial confounds: selection/sorting, spatial spillovers (SUTVA failure), and spatial autocorrelation. Essential for publishing high-impact work in journals like JUE.

This advanced analytical skill focuses on rigorously identifying and testing the specific transmission channels through which external shocks affect an economy. Essential for high-impact international economics research, it moves beyond descriptive mechanism narratives by focusing on testable proxies across trade, investment, finance, and expectation channels. It requires advanced econometrics (e.g., mediation analysis, sample splitting) and careful identification strategy to ensure causal claims are robust.

A comprehensive style guide for revising research papers to meet the specific, high standards of KDD conferences. It details the expected structure of the first page, emphasizing data regimes, named mechanisms, and quantifiable evidence (scale, metrics). It also provides rules for differentiating research vs. applied data science (ADS) voices and optimizing content for two-column, page-limited formats.