We provide a new way of deriving a number of dynamic unobserved factors from a set of variables. We show how standard principal components may be expressed in state space form and estimated using the Kalman filter. To illustrate our procedure, we perform two exercises. First, we use it to estimate a measure of the current account imbalances among northern and southern euro area countries that developed during the period leading up to the outbreak of the euro area crisis, before looking at adjustment in the post-crisis period. Second, we show how these dynamic factors can improve forecasting of the euro exchange rate.

中文翻译：

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对动态多因子模型 (DMFM) 的建议

我们提供了一种从一组变量中导出许多动态未观察到的因素的新方法。我们展示了如何以状态空间形式表示标准主成分并使用卡尔曼滤波器进行估计。为了说明我们的程序，我们进行了两个练习。首先，我们用它来估计在欧元区危机爆发前期间出现的南北欧元区国家经常账户失衡的衡量标准，然后再考虑后危机时期的调整。其次，我们展示了这些动态因素如何改善对欧元汇率的预测。