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VAR Model Averaging for Multi-Step Forecasting

Author

Listed:
  • Johannes Mayr
  • Dirk Ulbricht

Abstract

Given the relatively low computational effort involved, vector autoregressive (VAR) models are frequently used for macroeconomic forecasting purposes. However, the usually limited number of observations obliges the researcher to focus on a relatively small set of key variables, possibly discarding valuable information. This paper proposes an easy way out of this dilemma: Do not make a choice. A wide range of theoretical and empirical literature has already demonstrated the superiority of combined to single-model based forecasts. Thus, the estimation and combination of parsimonious VARs, employing every reasonably estimable combination of the relevant variables, pose a viable path of dealing with the degrees of freedom restriction. The results of a broad empirical analysis based on pseudo out-of-sample forecasts indicate that attributing equal weights systematically out-performs single models as well as most more refined weighting schemes in terms of forecast accuracy and especially in terms of forecast stability.

Suggested Citation

  • Johannes Mayr & Dirk Ulbricht, 2007. "VAR Model Averaging for Multi-Step Forecasting," ifo Working Paper Series 48, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_48
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    File URL: http://www.cesifo-group.de/DocDL/IfoWorkingPaper-48.pdf
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    References listed on IDEAS

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    1. 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.
    2. 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, May.
    3. Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, February.
    4. 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.
    5. 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.
    6. Caesar Lack, 2006. "Forecasting Swiss inflation using VAR models," Economic Studies 2006-02, Swiss National Bank.
    7. 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.
    8. Bunn, Derek W., 1985. "Statistical efficiency in the linear combination of forecasts," International Journal of Forecasting, Elsevier, vol. 1(2), pages 151-163.
    9. 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.
    10. Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
    11. 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.
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    Citations

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    Cited by:

    1. Gerit Vogt, 2010. "VAR-Prognose-Pooling : ein Ansatz zur Verbesserung der Informationsgrundlage der ifo Dresden Konjunkturprognosen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(02), pages 32-40, 04.
    2. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
    3. repec:ces:ifodre:v:17:y:2010:i:02:p:s.32-40 is not listed on IDEAS

    More about this item

    Keywords

    VAR-forecasting; model averaging;

    JEL classification:

    • A10 - General Economics and Teaching - - General Economics - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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