Skill UI

This tool acts as a comprehensive workflow router for researchers targeting The Journal of Law, Economics, and Organization (JLEO). It guides users through the entire academic process, from initial topic selection and literature positioning to developing models, ensuring robustness, and handling revision and rebuttal stages. It helps diagnose current bottlenecks and determines the optimal next specialized skill to use.

This guide helps authors refine academic prose for institutional and organizational economics journals. It teaches how to structure the narrative to open with an institutional puzzle, clearly name the underlying mechanism, and frame the contribution as a delta on a specific frontier, ensuring the focus remains on governance and organizational forms rather than just data or models.

A comprehensive guide for establishing rigorous identification strategies in monetary, banking, and macro-financial modeling. It details the standards required for publishing causal claims in top-tier journals (like JMCB), covering three branches: macro shock identification (SVAR), structural parameter identification, and micro-banking causal designs (e.g., staggered regulations). Learn how to defend against information effects, address endogeneity, and ensure policy relevance.

A comprehensive guide detailing the quantitative and econometric standards required for submissions to top-tier monetary and macroeconomic journals. It covers advanced techniques like VAR/SVAR, Local Projections, and DSGE modeling, focusing on proper inference, robustness checks, and diagnostic reporting to ensure scholarly rigor.

This guide details the rigorous identification methods required for submitting macro-financial papers to top-tier journals like the Journal of Monetary Economics (JME). It covers techniques such as separating pure monetary shocks from information effects, implementing various Structural VARs (SVARs), using local projections, and conducting model-based identification, ensuring your claims meet the highest academic standards.

This guide helps authors frame their academic contributions within highly specialized fields like monetary policy, DSGE modeling, and financial intermediation. It teaches how to precisely define the novel element (shock, mechanism, or counterfactual) relative to the closest prior work, ensuring the manuscript is viewed as an advance, not a mere survey. Ideal for preparing submissions to top-tier economics journals.

A comprehensive guide for authors submitting empirical or quantitative manuscripts to the Journal of Monetary Economics (JME). It details mandatory requirements for data deposition, model code (Dynare, MATLAB, Stata, R), master scripting, and adherence to Elsevier's generative AI declaration, ensuring maximum reproducibility and meeting high academic standards.

A comprehensive guide detailing the rigorous statistical and methodological norms required for publishing family research, specifically tailored for journals like JMF. It covers handling complex survey weights, non-independence in dyads and families, missing data imputation, attrition modeling, and robust reporting of uncertainty and selection effects.

A comprehensive guide for conducting rigorous, publication-quality statistical analyses required by top-tier management journals. It covers advanced techniques including Structural Equation Modeling (SEM)/CFA, Hierarchical Linear Modeling (HLM), complex regression, and meta-analysis, ensuring reports include necessary effect sizes, confidence intervals, and robustness checks to meet demanding academic standards.

This guide provides a rigorous methodological checklist for conducting data analysis suitable for top-tier academic journals, such as JMIS. It covers advanced techniques across econometrics (addressing identification and endogeneity), behavioral modeling (SEM/PLS, common-method bias), and ML/analytics, ensuring that research findings meet the highest standards of robustness and theoretical grounding.

This comprehensive guide helps researchers move beyond descriptive correlations to build rigorous, theory-driven manuscripts for top-tier IS journals. It outlines how to structure theoretical arguments based on specific research styles, including IT business value mechanisms, platform economics, behavioral models, and economic incentives, emphasizing the derivation of hypotheses and comparative statics before empirical testing.

A comprehensive guide for researchers conducting advanced data analysis and reporting for top marketing journals. It details selecting the appropriate econometric estimator (e.g., ANOVA, DiD, IV, mediation models) based on the study design (experimental, observational, panel). It emphasizes meeting rigorous journal mandates, including exact p-values, standard errors, and effect sizes, and linking statistical findings to practical managerial claims.