Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/89720
Authors: 
Duarte, Pablo
Süssmuth, Bernd
Year of Publication: 
2014
Series/Report no.: 
CESifo Working Paper 4574
Abstract: 
Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals with the implementation stage of this practice. We propose a two-tiered mechanism consisting in the identification of variables highly correlated with GDP as “core” indicators and a check of robustness of these variables in the sense of extreme bounds analysis. Accordingly selected indicators are used in an approximate DFM framework to exemplarily nowcast Spanish GDP growth. We show that our implementation produces more accurate nowcasts than both a benchmark stochastic process and the implementation based on the total set of core indicators.
Subjects: 
small-scale nowcasting models
Kalman Filter
extreme bounds analysis
JEL: 
C38
C53
Document Type: 
Working Paper

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