Real-Time Forecasting with a MIDAS VAR

Heiner Mikosch and Stefan Neuwirth ()
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Stefan Neuwirth: KOF Swiss Economic Institute, ETH Zurich, Switzerland

No 15-377, KOF Working papers from KOF Swiss Economic Institute, ETH Zurich

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 mixed frequency VAR substantially improves predictive accuracy upon a standard VAR for different VAR specifications. 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.

Keywords: Forecasting; Mixed frequency data; MIDAS; VAR; Real time (search for similar items in EconPapers)
Pages: 33 pages
Date: 2015-04
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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http://dx.doi.org/10.3929/ethz-a-010414894 (application/pdf)

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Working Paper: Real-time forecasting with a MIDAS VAR (2015)
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