Abstract
Using factor models, it has recently been shown that a pre-selection of indicators improves GDP forecasts in the very short-term. The aim of this paper is to adopt this research to the methodology of bridge models in combination with pooling approaches. Focusing on Euro Area GDP between 2005 and 2013, we find that a selection of targeted predictors by means of soft- and hard-threshold algorithms improves the forecasting performance, especially during periods of economic crisis. While a critical number of indicators are needed to include all relevant information, adding additional indicators has a negative effect on forecasting performance, all the more, if the set of indicators becomes unbalanced.
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