Skill UI

A comprehensive guide for authors submitting to top-tier journals, detailing how to structure policy implication sections for open economies. It emphasizes shifting the focus from generic domestic policy lists to specific, evidence-based recommendations concerning international mechanisms such as trade tariffs, exchange rate elasticity, capital account management, and global value chains (GVCs).

A comprehensive guide for structuring and writing professional rebuttal letters in academia. It teaches authors how to respond to highly specialized journal reviewer comments (R&R), particularly addressing challenging methodological points common in economics, such as open-economy fit, shift-share inference, and GVC measurement. It emphasizes professional tone, systematic rebuttal structure, and linking changes directly to the revised manuscript.

A comprehensive pre-submission checklist designed for academic authors preparing manuscripts for top-tier journals. It systematically verifies critical details such as footnote conventions, reference formatting, anonymity protocols, word count adherence, and the inclusion of supplementary data/code, ensuring compliance with the journal's most current submission guidelines.

This comprehensive guide details professional standards for presenting complex empirical economic results (tables and figures) for top-tier journals like The Journal of World Economy. It instructs users on simplifying main regression tables, standardizing notes (clustering, significance), and correctly presenting specialized open-economy objects such as event studies, gravity regressions, and GVC decompositions, ensuring research meets publication quality.

This guide helps researchers elevate vague global trends into rigorous, open-economy causal questions suitable for high-impact journals. It teaches methodology for identifying clear treatments, measuring international exposure (e.g., GVC, trade dependency), and defining precise counterfactuals within a general equilibrium framework.

This advanced analytical skill focuses on rigorously identifying and testing the specific transmission channels through which external shocks affect an economy. Essential for high-impact international economics research, it moves beyond descriptive mechanism narratives by focusing on testable proxies across trade, investment, finance, and expectation channels. It requires advanced econometrics (e.g., mediation analysis, sample splitting) and careful identification strategy to ensure causal claims are robust.

This comprehensive workflow guide is designed to structure the entire manuscript preparation process for submission to The Journal of World Economy. It acts as a router, ensuring that research systematically progresses from establishing an open-economy positioning and defining causal questions, through literature review, cross-border mechanism analysis, to final submission and rebuttal preparation.

A comprehensive guide detailing how to structure, package, and validate research artifacts for major machine learning conferences like KDD. It covers best practices for creating anonymous, reproducible repositories, handling scale claims, and providing robust evidence for different research tracks (Research, ADS, Datasets).

A comprehensive guide detailing the strategy and structure for author responses to peer reviews (rebuttals) in top-tier academic conferences like KDD. It covers the unique constraints, such as the prohibition of hyperlinks, how to anchor claims using specific coordinates (e.g., "Table 3, column 4"), and structuring responses to address multiple reviewer concerns while targeting the Area Chair's decision.

A comprehensive guide for authors preparing their accepted KDD paper for ACM proceedings. It covers the entire production pipeline, including page budgeting (9 content pages, 3 pages for references/appendix), managing e-rights and TAPS uploads, de-anonymization steps, and ensuring proper Digital Library metadata for final publication.

A comprehensive guide for structuring the empirical section of high-level machine learning papers (e.g., KDD). It details the 'four-axis evidence plan'—Quality, Scale, Efficiency, and Mechanism—and emphasizes critical data hygiene practices. Learn how to prevent temporal leakage, structure ablations in a matrix format, and design post-launch measurements to ensure academic rigor and reproducibility.

This guide provides a sophisticated framework for structuring the related work section when submitting research to KDD. It instructs authors on how to position their work within the deep academic lineage of data mining, comparing their novelty not just to prior KDD volumes, but also to major ML flagships (ICML, NeurIPS) and specialized venues (WWW, ICDM). Learn to articulate mechanism-level differences and avoid common citation traps.