Inflation forecasting using a neural network

This paper evaluates the usefulness of neural networks for inflation forecasting. In a pseudo-out-of-sample forecasting experiment using recent U.S. data, neural networks outperforin univariate autoregressive models on average for short horizons of one and two quarters. A simple specification of the neural network model and specialized estimation procedures from the neural networks literature appear to play significant roles in the success of the neural network model. (c) 2004 Elsevier B.V. All rights reserved.