ABSTRACT We analyze the performance of a broad range of nowcasting and short-term forecasting models for a representative set of twelve old and six new member countries of the European Union (EU) that are characterized by substantial differences in aggregate output variability. In our analysis, we generate ex-post out-of-sample nowcasts and forecasts based on hard and soft indicators that come from a comparable set of identical data. We show that nowcasting works well for the new EU countries because, although that variability in their GDP growth data is larger than that of the old EU economies, the economic significance of nowcasting is on average somewhat larger.

中文翻译：

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即时预测实际 GDP 增长：新旧欧盟国家之间的比较

摘要 我们分析了一组具有代表性的欧盟 (EU) 12 个旧成员国和 6 个新成员国的一系列临近预报和短期预测模型的性能，这些模型的特点是总产出可变性存在显着差异。在我们的分析中，我们根据来自一组可比较的相同数据的硬指标和软指标生成事后样本外即时预报和预测。我们表明临近预报对新的欧盟国家运作良好，因为尽管它们的 GDP 增长数据的变异性大于旧的欧盟经济体，但临近预报的经济意义平均略大。