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Nowcasting German GDP: A comparison of bridge and factor models

机译:临近预报的德国GDP:桥梁模型和要素模型的比较

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Governments and central banks need to have an accurate and timely assessment of gross domestic product's (GDP) growth rate for the current quarter, as this is essential for providing a reliable and early analysis of the current economic situation. This paper presents a series of models conceived to forecast the current German GDP's quarterly growth rate. These models are designed to be used on a monthly basis by integrating monthly economic information through bridge models, thus allowing for the economic interpretation of the data. We do also forecast German GDP by dynamic factor models. The combination of these two approaches allows selecting economically relevant explanatory variables among a large data set of hard and soft data. In addition, a rolling forecast study is carried out to assess the forecasting performance of the estimated models. To this end, publication lags are taken into account in order to run pseudo out-of-sample forecasts. We show that it is possible to get reasonably good estimates of current quarterly GDP growth in anticipation of the official release, especially from bridge models.
机译:各国政府和中央银行需要准确,及时地评估当前季度的国内生产总值(GDP)增长率,因为这对于提供可靠的早期分析当前经济状况至关重要。本文提出了一系列旨在预测当前德国GDP季度增长率的模型。这些模型旨在通过桥接模型集成每月的经济信息来每月使用,从而可以对数据进行经济的解释。我们也通过动态因素模型预测德国的GDP。这两种方法的组合允许在大量的硬数据和软数据中选择经济上相关的解释变量。此外,还进行了滚动预测研究,以评估估计模型的预测性能。为此,为了进行伪样本外预测,需要考虑发布延迟。我们表明,在正式发布之前,尤其是从过渡模型中,有可能获得对当前季度GDP增长的合理估计。

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