Araujo and Gaglianone (2023) benchmark a variety of machine learning approaches in addition to traditional approaches for inflation forecasting in Brazil, concluding that though neural networks and ensemble techniques present advancements above traditional styles, the efficiency may differ widely dependant upon input assortment and forecast horizon