Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/27661 
Year of Publication: 
2009
Series/Report no.: 
Discussion Paper Series 1 No. 2009,07
Publisher: 
Deutsche Bundesbank, Frankfurt a. M.
Abstract: 
This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model speci…cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients, whereas MF-VAR does not restrict the dynamics and therefore can su¤er from the curse of dimensionality. But if the restrictions imposed by MIDAS are too stringent, the MF-VAR can perform better. Hence, it is di¢ cult to rank MIDAS and MF-VAR a priori, and their relative ranking is better evaluated empirically. In this paper, we compare their performance in a relevant case for policy making, i.e., nowcasting and forecasting quarterly GDP growth in the euro area, on a monthly basis and using a set of 20 monthly indicators. It turns out that the two approaches are more complementary than substitutes, since MF-VAR tends to perform better for longer horizons, whereas MIDAS for shorter horizons.
Subjects: 
nowcasting
mixed-frequency data
mixed-frequency VAR
MIDAS
JEL: 
C53
E37
Document Type: 
Working Paper

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