Evaluating a global vector autoregression for forecasting

Neil Ericsson and Erica L. Reisman

No 1056, International Finance Discussion Papers from Board of Governors of the Federal Reserve System (U.S.)

Abstract: Global vector autoregressions (GVARs) have several attractive features: multiple potential channels for the international transmission of macroeconomic and financial shocks, a standardized economically appealing choice of variables for each country or region examined, systematic treatment of long-run properties through cointegration analysis, and flexible dynamic specification through vector error correction modeling. Pesaran, Schuermann, and Smith (2009) generate and evaluate forecasts from a paradigm GVAR with 26 countries, based on Des, di Mauro, Pesaran, and Smith (2007). The current paper empirically assesses the GVAR in Des, di Mauro, Pesaran, and Smith (2007) with impulse indicator saturation (IIS)?a new generic procedure for evaluating parameter constancy, which is a central element in model-based forecasting. The empirical results indicate substantial room for an improved, more robust specification of that GVAR. Some tests are suggestive of how to achieve such improvements.

Date: 2012
New Economics Papers: this item is included in nep-ets and nep-for
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Related works:
Journal Article: Evaluating a Global Vector Autoregression for Forecasting (2012)
Working Paper: Evaluating a Global Vector Autoregression for Forecasting (2012)
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