Skill UI

A comprehensive guide to structuring robustness checks for behavioral economics and empirical research. Instead of merely listing statistical tests, this framework mandates organizing checks by the underlying behavioral threat (e.g., experimenter demand, multiple comparisons, specification choice). It provides specific guidelines for experiments, observational data, and simulations, ensuring that findings are robust against alternative behavioral explanations and methodological choices.

A comprehensive guide for assembling the required data and code replication package for manuscripts submitted to the Journal of the European Economic Association (JEEA). This package ensures compliance with the DCAS standard, enabling the journal's Data Editor to verify the reproducibility of empirical, simulation, or experimental results before formal acceptance. It outlines the mandatory structure, README contents, and execution steps.

This guide provides strict guidelines for authors submitting highly theoretical papers (e.g., to Journal of Economic Theory) regarding computational, numerical, or empirical evidence. It enforces the 'theory-first' principle, ensuring that all quantitative work—including simulations, examples, and counterexamples—must serve to illustrate, test, or deepen the main theoretical contribution, rather than standing as a standalone finding. Key requirements include maintaining reproducibility, keeping examples minimal, and proper structural placement.

A guide for designing rigorous numerical experiments and simulations for academic manuscripts in management science. This methodology focuses on validating proven theoretical properties, assessing algorithm performance, exploring parameter sensitivity, and extracting actionable managerial insights. It emphasizes that simulations must complement, but never replace, formal mathematical proofs.

A comprehensive guide for designing rigorous Monte Carlo simulations and empirical illustrations for methodological papers, particularly in econometrics. It details how to stress assumptions, report necessary metrics (size, power, bias), and structure the evidence to prove a method's theoretical validity and practical utility.

A comprehensive guide for authors responding to highly technical referee reports, particularly for submissions to top econometrics journals like the Journal of Econometrics (JoE). It details strategies for addressing objections concerning assumptions, asymptotic gaps, and Monte Carlo simulations, ensuring the revised manuscript and response letter are technically airtight and methodologically rigorous.

Provides comprehensive guidelines for authors submitting to the Journal of Econometrics (JoE). It details the required best practices for data citation (using the Elsevier `[dataset]` format), ensuring methodological reproducibility (e.g., Monte Carlo simulations), and preparing estimators as runnable code packages (R, Python, etc.). This guide is essential for meeting rigorous academic publication standards and passing peer review.

A comprehensive guide detailing the rigorous standards for generating tables and figures intended for top-tier econometrics journals, such as the Journal of Econometrics (JoE). It covers best practices for Monte Carlo simulations, separating size and power reporting, comparing multiple estimators, and ensuring all exhibits are statistically rigorous, reproducible, and legible in a single-PDF print format.

This guide provides authors with best practices for improving the reproducibility and verifiable availability of communication experiments for submission to JOC. It clarifies the journal's current status regarding artifact badges, offering actionable advice on openly sharing code, data, and simulation parameters to enhance credibility while maintaining academic rigor.

A comprehensive guide for ensuring the reproducibility of communications simulations for journal submissions. It details critical steps, such as fixing random seeds, channel models, simulation parameters, software versions, and organizing a complete reproduction package. This ensures that research results can be accurately and credibly verified by external reviewers in high-impact scientific journals.

A specialized tool designed to assess the suitability and refine the structure of a manuscript targeting the Journal of Industrial Engineering and Engineering Management (IJEM). It helps authors understand the journal's specific scope, preferred methodologies (modeling, algorithms, simulation), structural requirements, and common rejection pitfalls, optimizing the paper before submission.

A comprehensive skill designed to guide researchers submitting solid mechanics manuscripts to the Journal of the Mechanics and Physics of Solids (JMPS). It helps authors elevate their work by focusing on establishing fundamental governing principles or physical mechanisms, moving beyond simple numerical simulations. Usage scenarios include pre-submission fit checks, determining the required mathematical rigor, and correctly framing the contribution against broader fields like plasticity or micro-mechanics.