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Assessing forecast uncertainties in a VECX* model for Switzerland: an exercise in forecast combination across models and observation windows

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  • Pesaran, M.H.
  • Assenmacher-Wesche, K.

Abstract

We investigate the effect of forecast uncertainty in a cointegrating vector error correction model for Switzerland. Forecast uncertainty is evaluated in three different dimensions. First, we investigate the effect on forecasting performance of averaging over forecasts from different models. Second, we look at different estimation windows. We find that averaging over estimation windows is at least as e¤ective as averaging over different models and both complement each other. Third, we explore whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the e¤ect of the weighting scheme on forecast accuracy is small in our application.

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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0746.

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Length: 24
Date of creation: Sep 2007
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Handle: RePEc:cam:camdae:0746

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Keywords: Bayesian model averaging; choice of observation window; longrun structural vector autoregression.;

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  1. Stephane Dees & Filippo di Mauro & M. Hashem Pesaran & L. Vanessa Smith, 2006. "Exploring the International Linkages of the Euro Area: a Global VAR Analysis," Computing in Economics and Finance 2006 47, Society for Computational Economics.
  2. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
  3. Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
  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. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2004. "‘Forecasting Time Series Subject to Multiple Structural Breaks’," Cambridge Working Papers in Economics 0433, Faculty of Economics, University of Cambridge.
  6. Garratt, Anthony & Lee, Kevin & Pesaran, M. Hashem & Shin, Yongcheol, 2006. "Global and National Macroeconometric Modelling: A Long-Run Structural Approach," OUP Catalogue, Oxford University Press, number 9780199296859, September.
  7. Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
  8. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
  9. Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, February.
  10. Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-79, April.
  11. Assenmacher-Wesche, K. & Pesaran, M.H., 2008. "A VECX* Model of the Swiss Economy," Cambridge Working Papers in Economics 0809, Faculty of Economics, University of Cambridge.
  12. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, April.
  13. 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.
  14. 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.
  15. Garratt A. & Lee K. & Pesaran M.H. & Shin Y., 2003. "Forecast Uncertainties in Macroeconomic Modeling: An Application to the U.K. Economy," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 829-838, January.
  16. Garratt, A. & Lee, K. & Pesaran, M. H. & Shin, Y., 1998. "A Long-run Structural Macro-econometric Model of the UK," Cambridge Working Papers in Economics 9812, Faculty of Economics, University of Cambridge.
  17. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, December.
  18. Geweke, John & Whiteman, Charles, 2006. "Bayesian Forecasting," Handbook of Economic Forecasting, Elsevier.
  19. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  20. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
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