Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/175347 
Year of Publication: 
2018
Series/Report no.: 
Working Paper No. 152
Publisher: 
Universität Leipzig, Wirtschaftswissenschaftliche Fakultät, Leipzig
Abstract: 
Dynamic factor models based on Kalman Filter techniques are frequently used to nowcast GDP. This study deals with the selection of indicators for this practice. We propose a two-tiered mechanism which is shown in a case study to produce more accurate nowcasts than a benchmark stochastic process and a standard model including extreme bounds fragile indicators. Nowcasting accuracy nearly measures up to the one of real-time forecasts by an institution with an interest in high-quality nowcasts.
Subjects: 
dynamic factor
Kalman Filter
extreme bounds analysis
JEL: 
C38
C53
Document Type: 
Working Paper

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