Araujo and Gaglianone (2023) benchmark a variety of equipment learning strategies together with traditional methods for inflation forecasting in Brazil, concluding that although neural networks and ensemble procedures give improvements more than traditional types, the effectiveness may differ widely according to input assortment and forecast horizo