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Forecasting Random Walks Under Drift Instability

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Author Info
M. Hashem Pesaran ()
Andreas Pick ()

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Abstract

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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Publisher Info
Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number CESifo Working Paper No. 2293.

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Date of creation: 2008
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Handle: RePEc:ces:ceswps:_2293

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Related research
Keywords: forecast combinations; averaging over estimation windows; exponentially down-weighting observations; structural breaks;

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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.:

  1. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier. [Downloadable!] (restricted)
  2. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May. [Downloadable!] (restricted)
    Other versions:
  3. 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. [Downloadable!]
    Other versions:
  4. Assenmacher-Wesche, Katrin & Pesaran, M. Hashem, 2008. "Forecasting the Swiss Economy Using VECX* Models: An Exercise in Forecast Combination Across Modelsand Observation Windows," Working Papers 2008-3, Swiss National Bank. [Downloadable!]
  5. 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. [Downloadable!] (restricted)
  6. M. Hashem Pesaran & Til Schuermann & L. Vanessa Smith, 2008. "Forecasting Economic and Financial Variables with Global VARs," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
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  7. Carlos Robalo Marques, 2004. "Inflation persistence - facts or artefacts?," Working Paper Series 371, European Central Bank. [Downloadable!]
  8. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier. [Downloadable!] (restricted)
  9. 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.
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  10. 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. [Downloadable!] (restricted)
  11. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583. [Downloadable!] (restricted)
  12. 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. [Downloadable!]
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  13. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
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  14. 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.
    Other versions:
  15. Todd E. Clark & Michael W. McCracken, 2006. "Averaging forecasts from VARs with uncertain instabilities," Research Working Paper RWP 06-12, Federal Reserve Bank of Kansas City. [Downloadable!]
    Other versions:
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  1. 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. [Downloadable!]
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