Predicting Belgium's GDP using targeted bridge models

This paper investigates the usefulness, within the frameworks of the standard bridge model and the 'bridging with factors' approach, of a predictor selection procedure that builds on the elastic net algorithm. A pseudo-real time forecasting exercise is performed, in which estimates for Belgium's quarterly GDP are generated using a monthly dataset of 93 potential predictors. While the simulation results indicate that specifying forecasting models using this procedure can lead to a slight improvement in terms of predictive accuracy over shorter horizons, the forecasting errors made by these 'targeted' models are not found to be significantly different from those based on the principal components extracted from the entire set of available indicators. In other words, the only advantage of following such an approach lies in the fact that it enables the forecaster to streamline the information set.