Skill UI

This guide provides a comprehensive pre-submission preflight checklist for manuscripts targeting the Journal of International Business Studies (JIBS). It ensures authors meet all structural, formatting, and ethical requirements, including double-blind anonymization, adhering to the JIBS Style Guide, managing word counts, and complying with Data Accessibility Statement (DART) policies before submitting to the Springer Nature portal.

This guide assists in creating high-quality, journal-ready exhibits (tables and figures) specifically for the Journal of International Business Studies (JIBS). It covers complex topics like cross-country descriptives, measurement-invariance tests, main results presentation, and cross-level interactions. The focus is on ensuring statistical rigor, strict adherence to journal style, and effective word count management for cross-border academic publications.

This guide provides comprehensive methodological frameworks for conducting rigorous empirical analyses in international trade and macroeconomics, particularly tailored to the standards of top-tier journals like the JIE. It covers assembling bilateral trade and cross-country panels, estimating gravity models using PPML, implementing local projections, and calibrating structural open-economy models. It ensures analyses are robust, replicable, and address common referee criticisms.

This skill guides authors in building and auditing tables and figures for submissions to the Journal of International Economics (JIE). It emphasizes that all exhibits must be self-contained and immediately understandable by a specialized referee. Focus areas include gravity tables, event-study plots, structural counterfactual charts, and how to report economic magnitudes (e.g., elasticity) rather than just statistical significance.

This guide provides a comprehensive framework for conducting rigorous cross-national data analysis, essential for academic research in international business. It covers critical advanced statistical methods like Measurement Invariance Testing (MGCFA), Multilevel Modeling (HLM), and Multi-Group SEM. It instructs users on handling cross-level moderation, interpreting country-level effects, and ensuring results are statistically auditable across complex data structures (e.g., panels, dyads).

A comprehensive guide for authors submitting to international finance journals, detailing how to structure the online supplementary appendix and prepare the data-and-code deposit. It ensures that supporting material is organized, traceable to main claims, and that data accessibility statements are compliant with institutional policies, especially for restricted international data.

This skill helps researchers anticipate and pre-empt predictable objections from international finance referees, particularly for submissions to journals like JIMF. It guides authors on strengthening the paper's international scope, improving causal identification against global confounders, and ensuring robustness to standard field checks (e.g., global crises, US-centricity) *before* submission. It is a proactive checklist for optimizing manuscript quality.

Provides a comprehensive guide for structuring the robustness section of international macro-finance papers, specifically tailored for JIMF submissions. It maps empirical checks to named international-finance threats (e.g., US-centrism, global episodes, regime dependence) to ensure results are stable and credible. Covers advanced econometric techniques like Driscoll–Kraay and time fixed effects.

A comprehensive guide for performing rigorous robustness checks on causal estimates in law and economics. It teaches researchers how to pre-empt common referee concerns—such as specification search, alternative treatment dating, or contaminated controls—by implementing targeted, methodologically sound tests to ensure estimates are stable and credible.

A comprehensive guide for formatting and creating high-impact tables and figures for academic submissions, particularly adhering to The Journal of Law and Economics (JLE) standards. It teaches how to visually present the main effect of a legal rule (e.g., event-studies, RD, DiD) clearly and concisely, ensuring the core identification is legible at a glance. Covers best practices for standard errors, clustering, and self-contained academic notes.

A comprehensive guide to establishing credible causal identification in empirical law and economics (L&E). It addresses the high institutional bar required by top journals, detailing how to defend the source of variation (e.g., reforms, governance choices, court assignments) against common threats like endogenous timing, selection bias, and omitted variables. Covers advanced methods including staggered Difference-in-Differences (DiD), Instrumental Variables (IV), and Regression Discontinuity Design (RDD).

This guide details how to assemble a comprehensive, reproducible replication package for academic manuscripts, especially in fields relying on complex institutional data (e.g., court records, contracts). It mandates creating a one-command master script, documenting the entire data pipeline from raw sources to final exhibits, and providing detailed protocols for hand-coded variables and data provenance. The goal is to ensure that any researcher can perfectly reproduce every finding.