Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/114451
Authors: 
Mikosch, Heiner
Neuwirth, Stefan
Year of Publication: 
2015
Series/Report no.: 
KOF Working Papers, KOF Swiss Economic Institute, ETH Zurich 377
Abstract: 
This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon lag polynomial scheme which is designed to reduce the parameter space while keeping models flexible. We show how to recast the resulting non-linear MIDAS type mixed frequency VAR into a linear equation system that can be easily estimated. A pseudo out-of-sample forecasting exercise with US real-time data yields that the mixed frequency VAR substantially improves predictive accuracy upon a standard VAR for different VAR specififications. Forecast errors for, e.g., GDP growth decrease by 30 to 60 percent for forecast horizons up to six months and by around 20 percent for a forecast horizon of one year.
Subjects: 
Forecasting
mixed frequency data
MIDAS
VAR
real time
JEL: 
C53
E27
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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