Skill UI

A comprehensive guide for strengthening causal identification strategies in empirical finance and economics. It covers advanced quasi-experimental designs like Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity (RDD), Propensity Score Matching (PSM), and Double Machine Learning (DML). Use this framework to stress-test your research design, address common econometric pitfalls, and ensure your paper meets the rigorous standards of top academic journals.

A comprehensive guide for authors responding to Developmental Psychology journal revise-and-resubmit (R&R) critiques. It provides a structured strategy to address rigorous demands—such as measurement invariance testing, attrition analyses, and enhanced transparency—while strengthening the developmental claim and managing the manuscript's length constraints.

A comprehensive guide for structuring and communicating robustness checks in economic policy papers. It teaches authors how to organize tests not as a checklist of alternative specifications, but by the specific threat (e.g., sample size, functional form, pre-trends) they neutralize. The focus must remain on defending the policy-relevant magnitude and confidence interval in the main text, preventing the paper from becoming a mere appendix dump.

A comprehensive pre-submission strategy guide designed to 'red-team' theoretical and econometric manuscripts. This tool helps authors anticipate and pre-empt harsh critiques from expert co-editors and referees, focusing specifically on identifying proof gaps, testing the generality of claims, ensuring finite-sample evidence, and addressing potential methodological competitors before journal submission.

This guide instructs authors on crafting highly targeted and convincing robustness sections for empirical finance papers. Instead of merely adding volume, it teaches the concept of 'subtraction, then precision'—identifying specific alternative explanations (threats) a referee might raise (e.g., reverse causality, omitted variables) and selecting the minimal, most effective check to neutralize each threat. This aligns with the philosophy of top-tier financial journals that value new ideas over superficial testing.

A rigorous self-assessment tool for academic manuscripts in game theory and economic behavior. It guides the identification of core assumptions, tests the logical architecture of proofs, and verifies the generalizability of results. It covers both theoretical proofs (e.g., equilibrium, mechanism design) and experimental designs, ensuring the argument withstands specialist scrutiny.

A comprehensive guide for authors submitting to top-tier chemistry journals like JACS. This skill helps authors pre-empt reviewer objections, select appropriate suggested and excluded experts, and rigorously stress-test the manuscript's scope, characterization, and mechanistic claims before formal submission. It transforms the writing process into a defensible, high-quality academic product.

This guide details the rigorous, reproducible empirical strategies required to identify causal parameters in applied econometrics, meeting high standards (e.g., JAE). It covers various designs—including DID, IV, panel data, and time-series—and mandates that every assumption and diagnostic test must be explicitly stated, tested, and reproducible using deposited code/data.

This comprehensive guide details the rigorous methodological standards required for validating new statistical estimators, tests, or algorithms. It moves beyond simple causal inference, emphasizing foundational proofs of identification, regularity conditions, asymptotic consistency, and finite-sample robustness. It serves as a checklist for assuring the credibility and reliability of methods in academic statistical journals.

A comprehensive guide for stress-testing and defending empirical identification strategies in finance and economics manuscripts. It covers advanced econometric techniques such as Staggered DiD, Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Event Studies, providing actionable advice on fixed effects, clustering, necessary robustness checks, and anticipating referee challenges.

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.

Designed for authors submitting to general-interest journals like JEEA. This skill helps stress-test a manuscript by simulating the two-gate decision process: the co-editor's fit assessment (desk-reject risk) and the referees' technical critiques. It guides authors on pre-empting common objections—such as general interest lack, identification weakness, or model fragility—by strategically framing the paper before submission.