Skill UI

This guide outlines the rigorous methodological standards for empirical identification in macroeconomics, crucial for submitting to top-tier journals. It covers advanced techniques such as Structural VAR (SVAR), Local Projections (LP), and handling high-frequency/micro-data shocks. It ensures authors explicitly defend the mapping from raw data to dynamic causal objects, addressing critical issues like endogeneity, anticipation, and structural breaks, and providing execution checklists for modern econometric tools (DiD, IV, RDD).

This guide details the critical steps required after conference acceptance to prepare a paper for the final, public 'camera-ready' submission (e.g., AISTATS, PMLR). It covers transforming an anonymous manuscript into the final two-column format, restoring author metadata, handling public artifacts (code, data), resolving formatting issues, and confirming all presentation and copyright obligations.

This guide details the multi-stage, rigorous review process for the American Journal of Political Science (AJPS). It covers the mechanics of double-blind screening, editorial fit assessment, expert peer review, and the unique, critical post-acceptance third-party verification step. It is designed to help authors anticipate and mitigate potential rejection issues by structuring and refining their manuscripts to meet top-tier academic standards.

A comprehensive guide for authors revising academic review articles, particularly for high-stakes journals. It teaches structured methods for addressing common referee feedback, such as coverage gaps, balance complaints, structural weaknesses, and accessibility issues. Use this guide to transform critical feedback into a robust, publishable revision plan, ensuring methodological transparency and scholarly rigor.

A comprehensive guide for authors preparing a rebuttal response for major academic conferences (like CCS). It teaches strategic communication, focusing on triaging decision-critical issues (threat model, ethics, novelty), structuring arguments by conceding strong points, anchoring claims to existing evidence, and avoiding over-promising. Essential for authors facing adversarial review patterns.

This guide provides rigorous methodology for authors to structure the policy and institutional background section of empirical economic manuscripts. Highlighting the journal's reliance on verifiable details (exact file names, dates, implementation rules), it teaches how to connect policy context directly to quasi-experimental identification strategies (like DID and event-study), ensuring the validity of causal claims and preventing common desk-reject issues.

This guide provides rigorous methodological standards for conducting mechanism analysis (mediation and moderation) in academic economics research. It strongly cautions against the traditional three-step mediation approach due to identification issues, recommending preferred alternatives like split-channel regression and causal moderation analysis to enhance the robustness of causal claims.

This comprehensive guide provides best practices for designing and presenting scientific experiments for high-impact academic journals. It covers structuring research around clear Research Questions (RQs), selecting strong and fair baselines, ensuring statistical rigor (mean ± standard deviation, significance testing), performing detailed ablation studies, and preventing common issues like data leakage and evaluation pollution. It is essential for authors aiming to validate complex computational findings.

This tool helps authors determine if their specialized research in earth, environmental, or planetary sciences is a suitable fit for the Communications Earth & Environment journal. It guides authors on framing the work for a broad readership, ensuring solid completeness, technical rigor, and adherence to Nature Portfolio's data standards, helping to avoid common desk-reject issues.

This guide assists researchers targeting top journals like China Rural Economy (CRE). It provides a structured self-check process for manuscripts, ensuring the topic strictly adheres to the "Three Rural Issues" scope, establishes deep theoretical grounding, and articulates clear, multi-faceted marginal contributions suitable for high-impact academic publication.

This guide provides an expert framework for advanced econometric analysis, focusing on establishing causal inference in fields like finance and trade. It details best practices for quasi-experimental designs (DID, IV, RDD, DML) and rigorously addresses common endogeneity issues such as policy bias, reverse causality, and anticipation effects, ensuring robust research methodology.

A comprehensive planning tool for developmental psychology researchers designing studies that must support a claim of change. It systematically guides users through critical methodological issues, including addressing age vs. cohort confounds, planning for measurement invariance across ages, handling attrition, and properly justifying sample size for growth slopes. Essential for strengthening the pre-analysis plan of longitudinal and cross-sectional designs.