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Forecasting economic and financial variables with global VARs

  • Pesaran, M. Hashem
  • Schuermann, Til
  • Smith, L. Vanessa

This paper considers the problem of forecasting economic and financial variables across a large number of countries in the global economy. To this end a global vector autoregressive (GVAR) model, previously estimated by Dees, di Mauro, Pesaran, and Smith (2007) and Dees, Holly, Pesaran, and Smith (2007) over the period 1979Q1-2003Q4, is used to generate out-of-sample forecasts one and four quarters ahead for real output, inflation, real equity prices, exchange rates and interest rates over the period 2004Q1-2005Q4. Forecasts are obtained for 134 variables from 26 regions, which are made up of 33 countries and cover about 90% of the world output. The forecasts are compared to typical benchmarks: univariate autoregressive and random walk models. Building on the forecast combination literature, the effects of model and estimation uncertainty on forecast outcomes are examined by pooling forecasts obtained from different GVAR models estimated over alternative sample periods. Given the size of the modelling problem, and the heterogeneity of the economies considered-industrialised, emerging, and less developed countries-as well as the very real likelihood of possibly multiple structural breaks, averaging forecasts across both models and windows makes a significant difference. Indeed, the double-averaged GVAR forecasts perform better than the benchmark competitors, especially for output, inflation and real equity prices.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 25 (2009)
Issue (Month): 4 (October)
Pages: 642-675

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Handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:642-675
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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  1. Mackinnon, J.G. & Haug, A.A. & Michelis, L., 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," G.R.E.Q.A.M. 96a09, Universite Aix-Marseille III.
  2. Chudik, Alexander & Pesaran, Hashem, 2009. "Infinite-dimensional VARs and factor models," Working Paper Series 0998, European Central Bank.
  3. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-60, May.
  4. James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
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  7. Katrin Assenmacher-Wesche & M. Hashem Pesaran, 2008. "Forecasting the Swiss Economy Using Vecx* Models: an Exercise in Forecast Combination Across Models and Observation Windows," National Institute Economic Review, National Institute of Economic and Social Research, vol. 203(1), pages 91-108, January.
  8. Arturo Estrella & Frederic S. Mishkin, 1996. "Predicting U.S. recessions: financial variables as leading indicators," Research Paper 9609, Federal Reserve Bank of New York.
  9. Pesaran, Mohammad Hashem & Holly, Sean & Dees, Stephane & Smith, L. Vanessa, 2007. "Long Run Macroeconomic Relations in the Global Economy," Economics Discussion Papers 2007-7, Kiel Institute for the World Economy.
  10. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-25, February.
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  12. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.
  13. Dees, S. & di Mauro, F. & Pesaran, M.H. & Smith, L.V., 2005. "Exploring the International Linkages of the Euro Area: a Global VAR Analysis," Cambridge Working Papers in Economics 0518, Faculty of Economics, University of Cambridge.
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  17. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809.
  18. M. Hashem Pesaran & Andreas Pick, 2009. "Forecasting Random Walks under Drift Instability," DNB Working Papers 207, Netherlands Central Bank, Research Department.
  19. Chudik, Alexander & Pesaran, Hashem & Tosetti, Elisa, 2009. "Weak and strong cross section dependence and estimation of large panels," Working Paper Series 1100, European Central Bank.
  20. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
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  23. Mohammad Hashem Pesaran & Richard J Smith & Yongcheol Shin, 1999. "Structural analysis of vector error correction models with exogenous I(1) variables," ESE Discussion Papers 38, Edinburgh School of Economics, University of Edinburgh.
  24. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, 02.
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  26. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
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