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The role of targeted predictors for nowcasting GDP with bridge models: Application to the Euro area

机译:用桥梁模型预测GDp的目标预测因子的作用:应用于欧元区

摘要

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.
机译:最近使用因子模型显示,预选指标可以在短期内改善GDP预测。本文的目的是将这项研究与池化方法相结合,应用于桥梁模型的方法论中。着眼于2005年至2013年欧元区的GDP,我们发现通过软阈值和硬阈值算法选择有针对性的预测指标可以提高预测效果,尤其是在经济危机时期。尽管需要大量指标才能包含所有相关信息,但是如果这组指标变得不平衡,则添加其他指标会对预测绩效产生负面影响。

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