AI-Driven Trade Analytics for Evaluating Free Trade Agreement Outcomes and Industrial Competitiveness

Abstract: This study investigates how AI-driven trade analytics can be integrated with econometric identification to evaluate Free Trade Agreement (FTA) outcomes and to quantify changes in industrial competitiveness using trade microdata. The empirical design is structured around a policy evaluation workflow that combines (i) event-study and difference-in-differences estimators for causal attribution and (ii) explainable machine-learning models for forecasting and heterogeneity discovery across