Magazine article from our research archive:

The generalized dynamic factor model: one-sided estimation and forecasting.

This article proposes a new forecasting method that makes use of information from a large panel of time series. Like earlier methods, our method is based on a dynamic factor model. We argue that our method improves on a standard principal component predictor in that it fully exploits all the dynamic covariance structure of the panel and also weights the variables according to their estimated signal-to-noise ratio. We provide asymptotic results for our optimal forecast estimator and show that in finite samples, our forecast outperforms the standard principal components predictor.

KEY WORDS: Dynamic factor model; Forecasting; Large cross-section; Panel data; Principal components; Time ...

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