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Real-Time Forecasting with a MIDAS VAR

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. An 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 di fferent VAR specifi cations. 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.

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File URL: http://dx.doi.org/10.3929/ethz-a-010414894
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Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 15-377.

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Length: 31 pages
Date of creation: Apr 2015
Handle: RePEc:kof:wpskof:15-377
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