Real-Time Nowcasting of GDP: A Factor Model vs. Professional Forecasters

Joëlle Liebermann ()

Oxford Bulletin of Economics and Statistics, 2014, vol. 76, issue 6, 783-811

Abstract: type="main" xml:id="obes12047-abs-0001">

We perform a fully real-time nowcasting (forecasting) exercise of US GDP growth using Giannone et al.'s (2008) factor model framework. To this end, we have constructed a real-time database of vintages from 1997 to 2010 for a panel of variables, enabling us to reproduce, for any given day in that range, the exact information that was available to a real-time forecaster. We track the daily evolution of the model performance along the real-time data flow and find that the precision of the nowcasts increases with information releases and the model fares well relative to the Survey of Professional Forecasters (SPF).

Date: 2014
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