Real-Time Forecasting of GDP Based on a Large Factor Model with Monthly and Quarterly Data
60 Pages Posted: 8 Jun 2016
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Real-Time Forecasting of GDP Based on a Large Factor Model with Monthly and Quarterly Data
Date Written: 2006
Abstract
This paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM algorithm combined with a principal components estimator. We discuss the in-sample properties of the estimator in real-time environments and methods for out-of-sample forecasting. As an empirical application, we estimate monthly German GDP in real-time, discuss the nowcast and forecast accuracy of the model and the role of revisions. Furthermore, we assess the contribution of timely monthly data to the forecast performance.
Keywords: monthly GDP, EM algorithm, principal components, factor models
JEL Classification: E37, C53
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