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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
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  1. Chudik , A. & Pesaran, M.H., 2007. "Infinite Dimensional VARs and Factor Models," Cambridge Working Papers in Economics 0757, Faculty of Economics, University of Cambridge.
  2. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
  3. Carlo Favero & Iryna Kaminska & Ulf Soderstrom, 2005. "The Predictive Power of the Yield Spread: Further Evidence and a Structural Interpretation," Working Papers 280, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  4. M. Hashem Pesaran & Til Schuermann & Scott M. Weiner, 2001. "Modelling regional interdependencies using a global error-correcting macroeconometric model," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B4-1, International Conferences on Panel Data.
  5. 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.
  6. Dees, S. & Holly, S. & Pesaran, M.H. & Smith, L.V., 2007. "Long Run Macroeconomic Relations in the Global Economy," Cambridge Working Papers in Economics 0703, Faculty of Economics, University of Cambridge.
  7. M. Hashem Pesaran & Andreas Pick, 2009. "Forecasting Random Walks under Drift Instability," DNB Working Papers 207, Netherlands Central Bank, Research Department.
  8. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier.
  9. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, October.
  10. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
  11. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  12. 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.
  13. Garcia, R. & Perron, P., 1990. "An Anlysis Of The Real Interest Rate Under Regime Shifts," Papers 353, Princeton, Department of Economics - Econometric Research Program.
  14. 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.
  15. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-77, Sept.-Oct.
  16. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
  17. Pesaran, M. Hashem & Shin, Yongcheol & Smith, Richard J., 2000. "Structural analysis of vector error correction models with exogenous I(1) variables," Journal of Econometrics, Elsevier, vol. 97(2), pages 293-343, August.
  18. Glenn D. Rudebusch & Brian P. Sack & Eric T. Swanson, 2007. "Macroeconomic implications of changes in the term premium," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 241-270.
  19. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
  20. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
  21. 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.
  22. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
  23. 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.
  24. James D. Hamilton & Dong Heon Kim, 2000. "A Re-examination of the Predictability of Economic Activity Using the Yield Spread," NBER Working Papers 7954, National Bureau of Economic Research, Inc.
  25. Alogoskoufis, George & Smith, Ron, 1991. " On Error Correction Models: Specification, Interpretation, Estimation," Journal of Economic Surveys, Wiley Blackwell, vol. 5(1), pages 97-128.
  26. Schorfheide, Frank, 2000. "Forecasting Economic Time Series," Econometric Theory, Cambridge University Press, vol. 16(03), pages 441-450, June.
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