Skill UI

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.'

This guide helps researchers refine their academic work to meet the rigorous standards of top economics journals like JPE. It teaches users to move beyond simple correlation by structuring their research around clear economic mechanisms, linking evidence to established theory, ensuring generality, and properly considering equilibrium effects. Use this when developing a paper pitch or deciding the overall scope of a manuscript.

A comprehensive guide for researchers developing models in decision theory under risk and uncertainty. It outlines how to strengthen theoretical representations by ensuring the model is anchored by clear axiomatic foundations, a mathematically tractable functional form, and crucially, verifiable behavioral content (i.e., what the model predicts or forbids). This helps bridge the gap between abstract theory and empirical data.

A comprehensive guide for developing rigorous spatial economic models, designed for manuscripts needing deep theoretical interpretation (e.g., JUE submissions). It instructs users on how to build quantitative spatial models (QSMs), sorting models, and spatial-equilibrium frameworks to interpret reduced-form estimates, establish counterfactual policies, and ensure that theory rigorously disciplines the empirical findings. Focus areas include general-equilibrium reallocation, policy invariance, and identifying parameters.

This skill provides expert guidance on positioning theoretical work for Linguistic Inquiry, a premier venue in generative grammar. It helps authors structure rigorous formal analyses of syntax and its interfaces (morphology, semantics, phonology). Use this when developing explicit, falsifiable theoretical proposals, crafting focused 'squibs,' or navigating the high standards required for top-tier academic linguistics publications.

A comprehensive guide for structuring the theoretical core of academic papers in Management Science. It covers two main approaches: developing formal analytical models (assumptions, propositions, comparative statics) or generating robust empirical hypotheses based on explicit mechanisms. The goal is always to derive decision-relevant, cross-departmental insights.

This comprehensive guide assists authors in developing rigorous methodology sections for academic papers in Marketing Science. It covers advanced techniques such as structural econometrics, causal ML, dynamic games, and quasi-experiments. Key focus areas include ensuring model identifiability, specifying estimators (GMM, MLE), and rigorously defending exogeneity assumptions.

A guide for transforming abstract marketing phenomena into rigorous, mathematically testable models. It covers both analytical (game-theoretic) and structural econometric approaches, emphasizing the specification of primitives, deriving equilibria, and establishing clear identification arguments for academic research.

This guide serves as a comprehensive workflow router for authors preparing a Marketing Science manuscript. It dictates the sequential steps, from identifying a modeling-worthy topic and developing a structural or analytical model, through data analysis, contribution framing, and final submission. It ensures the paper maintains a focus on formal modeling and managerial counterfactuals, adhering to the journal's rigorous standards.

A guide for developing rigorous analytical or stochastic models for Manufacturing & Service Operations Management (M&SOM). It emphasizes translating operational decisions, objectives, and uncertainties into explicit structural results, such as policy forms (e.g., order-up-to levels) and comparative statics, ensuring the core insight remains operational rather than merely descriptive.

A comprehensive guide for developing high-impact exhibits (tables, figures, process models) for academic manuscripts, particularly in organizational science. It covers house styles, methodological requirements (qualitative, quantitative, network), and quality assurance to ensure that all claims are clearly supported, rigorously formatted, and compliant with top-tier journal standards.

A comprehensive guide for formulating rigorous Operations Research (OR) manuscripts. It covers defining mathematical models (optimization, stochastic, simulation), structuring claims (theorems, propositions), and rigorously justifying assumptions. Essential for transforming practical problems into mathematically provable, publication-ready academic work.