Advanced Search
MyIDEAS: Login

Forecasting economic and financial variables with global VARs

Contents:

Author Info

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

Abstract

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

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.newyorkfed.org/research/staff_reports/sr317.html
Download Restriction: no

File URL: http://www.newyorkfed.org/research/staff_reports/sr317.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 317.

as in new window
Length:
Date of creation: 2008
Date of revision:
Handle: RePEc:fip:fednsr:317

Contact details of provider:
Postal: 33 Liberty Street, New York, NY 10045-0001
Email:
Web page: http://www.newyorkfed.org/
More information through EDIRC

Order Information:
Email:
Web: http://www.ny.frb.org/rmaghome/staff_rp/

Related research

Keywords: Economic forecasting ; Time-series analysis ; Econometric models ; Vector autoregression;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. 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.
  2. Chudik, A. & Pesaran, M.H. & Tosetti, E., 2009. "Weak and Strong Cross Section Dependence and Estimation of Large Panels," Cambridge Working Papers in Economics 0924, Faculty of Economics, University of Cambridge.
  3. Chudik, Alexander & Pesaran, M. Hashem, 2007. "Infinite Dimensional VARs and Factor Models," IZA Discussion Papers 3206, Institute for the Study of Labor (IZA).
  4. Pesaran, M. H. & Shin, Y. & Smith, R. J., 1997. "Structural Analysis of Vector Error Correction Models with Exogenous I(1) Variables," Cambridge Working Papers in Economics 9706, Faculty of Economics, University of Cambridge.
  5. 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.
  6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  7. 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.
  8. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier.
  9. Stephane Dees & Filippo di Mauro & M. Hashem Pesaran & L. Vanessa Smith, 2004. "Exploring the International Linkages of the Euro Area: A Global VAR Analysis," IEPR Working Papers 04.6, Institute of Economic Policy Research (IEPR).
  10. M. Hashem Pesaran & Andreas Pick, 2008. "Forecasting Random Walks Under Drift Instability," CESifo Working Paper Series 2293, CESifo Group Munich.
  11. 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.
  12. James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
  13. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, November.
  14. Schorfheide, Frank, 2000. "Forecasting Economic Time Series," Econometric Theory, Cambridge University Press, vol. 16(03), pages 441-450, June.
  15. Favero, Carlo A & Kaminska, Iryna & Söderström, Ulf, 2005. "The Predictive Power of the Yield Spread: Further Evidence and A Structural Interpretation," CEPR Discussion Papers 4910, C.E.P.R. Discussion Papers.
  16. 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.
  17. 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.
  18. Arturo Estrella & Frederic S. Mishkin, 1999. "Predicting U.S. Recessions: Financial Variables as Leading Indicators," NBER Working Papers 5379, National Bureau of Economic Research, Inc.
  19. 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.
  20. Garcia, R. & Perron, P., 1994. "An Analysis of the Real Interest rate Under Regime Shifts," Cahiers de recherche 9428, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  21. Alogoskoufis, George & Smith, Ron, 1991. " On Error Correction Models: Specification, Interpretation, Estimation," Journal of Economic Surveys, Wiley Blackwell, vol. 5(1), pages 97-128.
  22. 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.
  23. 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.
  24. James G. MacKinnon & Alfred A. Haug & Leo Michelis, 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Working Papers 1996_07, York University, Department of Economics.
  25. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
  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.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:fip:fednsr:317. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Amy Farber).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.