VAR Model Averaging for Multi-Step Forecasting
Given the relatively low computational effort involved, vector autoregressive (VAR)models are frequently used for macroeconomic forecasting purposes. However, the usuallylimited number of observations obliges the researcher to focus on a relatively smallset of key variables, possibly discarding valuable information. This paper proposes aneasy way out of this dilemma: Do not make a choice. A wide range of theoretical andempirical literature has already demonstrated the superiority of combined to single-modelbased forecasts. Thus, the estimation and combination of parsimonious VARs, employingevery reasonably estimable combination of the relevant variables, pose a viable path ofdealing with the degrees of freedom restriction. The results of a broad empirical analysisbased on pseudo out-of-sample forecasts indicate that attributing equal weights systematicallyout-performs single models as well as most more refined weighting schemes interms of forecast accuracy and especially in terms of forecast stability.
|Date of creation:||2007|
|Contact details of provider:|| Postal: Poschingerstr. 5, 81679 München|
Web page: http://www.cesifo-group.de
More information through EDIRC
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.:
- Brown, Bryan W & Maital, Shlomo, 1981. "What Do Economists Know? An Empirical Study of Experts' Expectations," Econometrica, Econometric Society, vol. 49(2), pages 491-504, March.
- Todd E. Clark & Michael W. McCracken, 2009.
"Improving Forecast Accuracy By Combining Recursive And Rolling Forecasts,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 363-395, 05.
- Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
- Todd E. Clark & Michael W. McCracken, 2008. "Improving forecast accuracy by combining recursive and rolling forecasts," Working Papers 2008-028, Federal Reserve Bank of St. Louis.
- Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, February.
- Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
- Chevillon, Guillaume & Hendry, David F., 2005. "Non-parametric direct multi-step estimation for forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 21(2), pages 201-218.
- David Hendry & Guillaume Chevillon, 2004. "Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes," Economics Series Working Papers 196, University of Oxford, Department of Economics.
- Guillaume Chevillon & David F. Hendry, 2004. "Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes," Economics Papers 2004-W12, Economics Group, Nuffield College, University of Oxford.
- Caesar Lack, 2006. "Forecasting Swiss inflation using VAR models," Economic Studies 2006-02, Swiss National Bank.
- 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.
- 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.
- James H. Stock & Mark W. Watson, 1994. "Evidence on structural instability in macroeconomic times series relations," Working Paper Series, Macroeconomic Issues 94-13, Federal Reserve Bank of Chicago.
- Bunn, Derek W., 1985. "Statistical efficiency in the linear combination of forecasts," International Journal of Forecasting, Elsevier, vol. 1(2), pages 151-163.
- Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
- Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
- Deutsch, Melinda & Granger, Clive W. J. & Terasvirta, Timo, 1994. "The combination of forecasts using changing weights," International Journal of Forecasting, Elsevier, vol. 10(1), pages 47-57, June. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:ces:ifowps:_48. 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: (Klaus Wohlrabe)
If references are entirely missing, you can add them using this form.