We propose a release-augmented dynamic factor model (RA-DFM) that allows to quantify the role of a country's data flow in nowcasting both early Gross Domestic Product (GDP) releases and subsequent revisions of official estimates. We use the RA-DFM to study UK GDP early revision rounds and assemble a comprehensive and novel mixed-frequency dataset that features 12 years of real-time data vintages. The RA-DFM improves over the standard DFM in real time when forecasting the first release each quarter. Economic and survey data help to predict the first revision round.

中文翻译：

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不确定的王国：临近预测的国内生产总值及其修订

我们提出了一个发布增强的动态因子模型 (RA-DFM)，该模型允许量化一个国家的数据流在临近预测早期国内生产总值 (GDP) 发布和官方估计的后续修订中的作用。我们使用 RA-DFM 研究英国 GDP 早期修订轮次，并组装了一个全面且新颖的混合频率数据集，该数据集具有 12 年的实时数据年份。在预测每个季度的第一个版本时，RA-DFM 实时改进了标准 DFM。经济和调查数据有助于预测第一轮修订。