Skill UI

This skill guides researchers in elevating observed findings into rigorously theoretical, generalizable, and falsifiable arguments suitable for top-tier academic journals. It provides structured methods for building mechanisms (empirical), defining comparative statics (formal), and establishing conceptual claims (normative). Use this when you need to prove that your contribution is novel, sharp, and matters to a general readership.

This skill helps authors evaluate if their empirical work—which applies econometric methods to substantive economic questions—is suitable for top-tier applied econometrics journals. It guides authors on the necessary focus on empirical application, data reproducibility, methodological rigor, and proper framing, helping authors minimize rejection risks and select the best publishing venue.

This comprehensive skill helps researchers determine if their academic paper, focusing on banking, liquidity, or financial intermediation, is suitable for the Journal of Financial Intermediation (JFI). It guides authors on necessary theoretical contributions, rigorous empirical identification methods (e.g., DiD/IV/RDD), required paper structure, and adherence to the journal's highly specific submission standards and potential rejection triggers.

A comprehensive skill designed for academics submitting papers in urban, regional, or spatial economics. It guides authors through evaluating their manuscript's suitability for the Journal of Urban Economics (JUE). The tool emphasizes the necessity of a credible spatial mechanism, robust identification methods (e.g., DiD, RDD), and adherence to high-level empirical and structural modeling standards required by top-tier journals.

This guide provides a rigorous framework for advanced econometric modeling in quantitative economics. It covers time series, panel data, cointegration, and mixed-frequency techniques (VAR, VECM, GMM, MIDAS). It emphasizes proper model diagnostics, stationarity testing, and grounding models in specific data properties and economic contexts.

A comprehensive guide for advanced empirical research in open economies. It outlines best practices for establishing causal inference by anchoring identification strategies in external or institutional shocks (e.g., tariffs, trade agreements, exchange rate reforms). The guide emphasizes modern critiques of standard methods like shift-share and gravity models, providing detailed protocols for DID, Bartik decomposition, and IV estimation to meet top-tier academic journal standards.

This guide provides methodological standards for defending the empirical design of a language manuscript. It covers various subfields—including fieldwork, corpus construction, phonetics, and typological comparison—ensuring that the evidence base is transparent, rigorous, and directly supports the stated theoretical claims. Use this when justifying data collection methods or addressing reviewer concerns about evidence validity.

A comprehensive guide for executing and reporting advanced analysis for high-level academic manuscripts, particularly in management science. It mandates rigorous verification across two lanes: the analytical lane (proving theorems and comparative statics) and the empirical lane (identifying and estimating causal effects using methods like DiD, IV, and RDD). It emphasizes adherence to Data-and-Code-Disclosure policies, ensuring all results are reproducible, verifiable, and meet high methodological standards.

This guide assists researchers in selecting and rigorously defending the appropriate methodology for Management Science (INFORMS) manuscripts. It covers both analytical modeling approaches (e.g., optimization, stochastic processes, game theory) and empirical designs (e.g., quasi-experiments, field trials). It ensures the chosen design not only matches the research question but also meets strict departmental standards and generates decision-relevant managerial insights.

This guide provides comprehensive advice for positioning computer science manuscripts, particularly those involving software repository mining, developer behavior, and empirical methods, for the Mining Software Repositories (MSR) conference. It covers required elements like dataset construction, validity threat analysis, reproducible workflows, and aligning the work with the specific scope of software analytics venues, helping authors strategically re-frame their research for maximum impact.

A comprehensive guide for executing, evaluating, and reporting the empirical core of MIS Quarterly manuscripts. It covers specialized methods for Behavioral IS (PLS-SEM), Economics of IS (causal identification), Design Science (artifact evaluation), and qualitative studies, ensuring full transparency and replicability for top-tier academic submissions.

A comprehensive guide for researchers writing about Manufacturing and Service Operations Management (M&SOM). It mandates that the method chosen must be dictated by the core operational decision. Provides detailed frameworks for both the analytical lane (e.g., stochastic optimization, queueing theory, game theory) and the empirical/causal lane (e.g., Difference-in-Differences, Instrumental Variables), ensuring the research delivers actionable operational insights.