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Forecasting Time Series Subject to Multiple Structural Breaks

  • Pesaran, M. Hashem

    ()

    (University of Cambridge)

  • Pettenuzzo, Davide

    (Bocconi University)

  • Timmermann, Allan

    ()

    (University of California, San Diego)

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if any) by means of a hierarchical hidden Markov chain model. Predictions are formed by integrating over the hyper parameters from the meta distributions that characterize the stochastic break point process. In an application to US Treasury bill rates, we find that the method leads to better out-of-sample forecasts than alternative methods that ignore breaks, particularly at long horizons.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1196.

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Length: 41 pages
Date of creation: Jun 2004
Date of revision:
Publication status: published in Review of Economic Studies, 2006, 73 (4), 1057-1084
Handle: RePEc:iza:izadps:dp1196
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  1. Garratt, Anthony & Kevin Lee & M Hashem Pesaran & Yongcheol Shin, 2002. "Forecast Uncertainties In Macroeconometric Modelling: An Application to the UK Economy," Royal Economic Society Annual Conference 2002 82, Royal Economic Society.
  2. René Garcia & Pierre Perron, 1995. "An Analysis of the Real Interest Rate Under Regime Shifts," CIRANO Working Papers 95s-05, CIRANO.
  3. 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.
  4. Clements, Michael P. & Hendry, David F., 1998. "Forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 14(1), pages 111-131, March.
  5. Lubos Pastor & Robert F. Stambaugh, 2000. "The Equity Premium and Structural Breaks," NBER Working Papers 7778, National Bureau of Economic Research, Inc.
  6. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
  7. Kim, Chang-Jin & Nelson, Charles R & Piger, Jeremy, 2004. "The Less-Volatile U.S. Economy: A Bayesian Investigation of Timing, Breadth, and Potential Explanations," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 80-93, January.
  8. Francis X. Diebold & Peter Pauly, 1987. "The use of prior information in forecast combination," Special Studies Papers 218, Board of Governors of the Federal Reserve System (U.S.).
  9. Pesaran, M.H. & Timmermann, A., 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," Cambridge Working Papers in Economics 0331, Faculty of Economics, University of Cambridge.
  10. Gary Koop & Simon M. Potter, 1999. "Are apparent findings of nonlinearity due to structural instability in economic time series?," Staff Reports 59, Federal Reserve Bank of New York.
  11. 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.
  12. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  13. Allan Timmermann & M. Hashem Pesaran, 2002. "Market Timing and Return Prediction under Model Instability," FMG Discussion Papers dp412, Financial Markets Group.
  14. 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.
  15. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
  16. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
  17. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
  18. repec:cup:cbooks:9780521634809 is not listed on IDEAS
  19. Andrew Ang & Geert Bekaert, 1998. "Regime Switches in Interest Rates," NBER Working Papers 6508, National Bureau of Economic Research, Inc.
  20. 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, June.
  21. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
  22. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
  23. Alogoskoufis, George S & Smith, Ron, 1991. "The Phillips Curve, the Persistence of Inflation, and the Lucas Critique: Evidence from Exchange-Rate Regimes," American Economic Review, American Economic Association, vol. 81(5), pages 1254-75, December.
  24. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September.
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