We take a model selection approach to real-time macroeconomic forecasting using linear and nonlinear models. True ex-ante forecasting are constructed by using unrevised as opposed to fully revised data. Model selection as well as model performance measures are considered.

We take a model selection approach to the question of whether a class of adaptive prediction models (artificial neural networks) is useful for predicting future values of nine macroeconomic variables. We use a variety of out-of-sample forecast-based model selection criteria, including forecast...