Skill UI

A comprehensive guide to defending causal claims in policy and program evaluation, adhering to rigorous econometric standards (e.g., JPAM). It covers advanced methods such as RCT, Difference-in-Differences (DiD), Regression Discontinuity (RDD), Instrumental Variables (IV), and Synthetic Control. This guide emphasizes stating the estimand, defending identification assumptions, and robustly ruling out alternative causal explanations, rather than just writing estimation code.

A comprehensive guide for ensuring the robustness of empirical findings, particularly for submissions to top-tier economic journals. This method moves beyond simply showing that coefficients remain significant, focusing instead on defending the core economic interpretation by systematically ruling out alternative mechanisms, structural assumptions, and potential sources of bias. It guides the development of a rigorous 'robustness battery.'

A comprehensive guide and framework for authors targeting the journal 'Modern Financial Research'. It helps assess whether a manuscript's scope, methodology (e.g., VAR, DID), and policy relevance align with the journal's focus on banking, finance, and macro-policy. It details submission requirements, common pitfalls, and suggestions for revision or alternative journals.

A comprehensive guide for executing and reporting quantitative analyses for high-stakes public policy research. This skill emphasizes methodological rigor, demanding transparency in uncertainty reporting (effect size, intervals), robust checks (heterogeneity, alternative specifications), and ensuring full reproducibility through master scripts and pinned versions for journal submission.

This skill guides authors on how to proactively strengthen their academic manuscripts before submission, especially for highly demanding journals. It involves identifying the most likely expert reviewers, predicting their specific methodological, theoretical, or empirical objections, and strategically integrating countermeasures, robustness checks, and alternative explanations directly into the main text. It transforms the submission process from a defensive reaction to a proactive, structured argument.

This skill helps authors assess the suitability of their accounting manuscripts for prestigious academic journals like Review of Accounting Studies (RAST). It analyzes the paper's fit, rigor, methodological strength, and structure against top-tier academic standards in areas like valuation, disclosure, and information economics. It provides actionable feedback on potential rejection risks and alternative venues.

This comprehensive guide outlines the robust battery of checks required for high-impact empirical finance papers. It covers alternative specifications, subsample analysis, outlier sensitivity, and crucial multiple-testing adjustments. Use this framework to structure your methodology, ensuring your central claims are statistically rigorous, reproducible, and capable of withstanding intense academic peer review and scrutiny.

A comprehensive guide for conducting and reporting rigorous empirical analysis in academic research, particularly in finance and accounting. It covers selecting appropriate estimators (e.g., DiD, 2SLS, RDD), handling fixed effects, ensuring statistical robustness through placebo and alternative testing, and fulfilling strict data-authenticity and code-access requirements required by top-tier journals.

This comprehensive guide provides authors with structured frameworks for assessing robustness and trustworthiness in World Development manuscripts. It guides users to organize checks by identifying specific threats (e.g., specification dependence, measurement error) in quantitative work, or demonstrating methodological rigor (e.g., triangulation, negative-case analysis) in qualitative work. It ensures findings are thoroughly vetted against alternative explanations.

This comprehensive guide outlines the annual workflow for submitting research papers to major AI/NLP conferences, such as WSDM. It details critical milestones, including abstract deadlines, paper submission, conference logistics, and strategies for alternative tracks (short papers, demos). It is essential for researchers managing their academic publication timeline and coordinating with neighboring venues.

This skill resolves missing measures by reusing saved custom metrics or creating ephemeral formulas. It guides users to confirm metric definitions, units, and aggregation logic before calculation. It prioritizes native outputs and saved metrics over formula creation. The skill ensures validation of formulas and reports results as non-persistent data without saving new definitions.