We propose a nowcasting system to obtain real-time predictive intervals for the first-release of UK quarterly GDP growth that can be implemented in a menu-driven econometric software. We design a bottom-up approach: forecasts for GDP components (from the output and the expenditure approaches) are inputs into the computation of probabilistic forecasts for GDP growth. For each GDP component considered, mixed-data-sampling regressions are applied to extract predictive content from monthly and quarterly indicators. We find that predictions from the nowcasting system are accurate, in particular when nowcasts are computed using monthly indicators 30 days before the GDP release. The system is also able to provide well-calibrated predictive intervals.

中文翻译：

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使用混合频率自底向上方法的英国季度 GDP 增长的实时概率预报

我们提出了一个临近预报系统，以获得英国季度 GDP 增长的首次发布的实时预测间隔，该系统可以在菜单驱动的计量经济学软件中实施。我们设计了一种自下而上的方法：对 GDP 组成部分的预测（来自产出和支出方法）是计算 GDP 增长概率预测的输入。对于所考虑的每个 GDP 组成部分，应用混合数据抽样回归从月度和季度指标中提取预测内容。我们发现临近预报系统的预测是准确的，特别是在 GDP 发布前 30 天使用月度指标计算临近预报时。该系统还能够提供经过良好校准的预测间隔。