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Forecasting Random Walks Under Drift Instability

  • Pesaran, M.H.
  • Pick, A.

This paper considers forecast averaging when the same model is used but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks. Similar results are also obtained when observations are exponentially down-weighted, although in this case the performance of forecasts based on exponential down-weighting critically depends on the choice of the weighting coefficient. The forecasting techniques are applied to monthly inflation series of 21 OECD countries and it is found that average forecasting methods in general perform better than using forecasts based on a single estimation window.

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File URL: http://www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe0814.pdf
File Function: Working Paper Version
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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0814.

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Length: 24
Date of creation: Mar 2008
Date of revision:
Handle: RePEc:cam:camdae:0814
Contact details of provider: Web page: http://www.econ.cam.ac.uk/index.htm

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  1. Carlos Robalo Marques, 2005. "Inflation persistence: facts or artefacts?," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
  2. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
  3. Wiliam Branch & George W. Evans, 2005. "A Simple Recursive Forecasting Model," University of Oregon Economics Department Working Papers 2005-3, University of Oregon Economics Department, revised 01 Feb 2005.
  4. 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.
  5. 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.
  6. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  7. M. Hashem Pesaran & Til Schuermann & L. Vanessa Smith, 2008. "Forecasting economic and financial variables with global VARs," Staff Reports 317, Federal Reserve Bank of New York.
  8. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  9. Timmermann, Allan G, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
  10. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  11. repec:cup:cbooks:9780521321969 is not listed on IDEAS
  12. Burdekin, Richard C K & Siklos, Pierre L, 1999. "Exchange Rate Regimes and Shifts in Inflation Persistence: Does Nothing Else Matter?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(2), pages 235-47, May.
  13. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
  14. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  15. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  16. 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.
  17. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
  18. 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.
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