AI forecasting outperforms traditional methods – study
New approach still only complements existing models but results are promising, say authors
Sveriges Riksbank economists have said artificial intelligence-based forecasting models are ready for wider use.
In a staff memo published on April 2, economists Davide Bucci Vicenzo, Ard Den Reijer, Pär Stockhammer, David Vestin and Xin Zhang find that both random forest (RF) and neural network (NN) models generate accurate predictions for GDP and inflation.
RF models construct multiple “decision trees” during training, and then output the average of their predictions. NN models draw inspiration
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