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Evaluating a Global Vector Autoregression for Forecasting

  • Neil R. Ericsson

    ()

    (Board of Governors of the Federal Reserve System)

  • Erica L. Reisman

    ()

    (Board of Governors of the Federal Reserve System)

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 Dées, di Mauro, Pesaran, and Smith (2007). The current paper empirically assesses the GVAR in Dées, 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.

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File URL: http://www.gwu.edu/~forcpgm/2012-006.pdf
File Function: First version, 2012
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Paper provided by The George Washington University, Department of Economics, Research Program on Forecasting in its series Working Papers with number 2012-006.

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Length: 21 pages
Date of creation: Nov 2012
Date of revision:
Handle: RePEc:gwc:wpaper:2012-006
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  1. M. Hashem Pesaran & L. Vanessa Smith & Ron P. Smith, 2007. "What if the UK or Sweden had joined the euro in 1999? An empirical evaluation using a Global VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(1), pages 55-87.
  2. Erceg, Christopher & Guerriei, Luca & Gust, Christopher, 2006. "SIGMA: A New Open Economy Model for Policy Analysis," MPRA Paper 813, University Library of Munich, Germany.
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  6. M. Hashem Pesaran & Til Schuermann & Scott M. Weiner, 2002. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Center for Financial Institutions Working Papers 01-38, Wharton School Center for Financial Institutions, University of Pennsylvania.
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  19. Garratt, Anthony & Lee, Kevin & Pesaran, M. Hashem & Shin, Yongcheol, 2006. "Global and National Macroeconometric Modelling: A Long-Run Structural Approach," OUP Catalogue, Oxford University Press, number 9780199296859, March.
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  25. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
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