Harnessing Graph Neural Networks to Predict International Trade Flows
Bassem Sellami,
Chahinez Ounoughi,
Tarmo Kalvet
et al.
Abstract:In the realm of international trade and economic development, the prediction of trade flows between countries is crucial for identifying export opportunities. Commonly used log-linear regression models are constrained due to difficulties when dealing with extensive, high-cardinality datasets, and the utilization of machine learning techniques in predictions offers new possibilities. We examine the predictive power of Graph Neural Networks (GNNs) in estimating the value of bilateral trade between countries. We … Show more
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