Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)
This paper considers the problem of forecasting under continuous and discrete structural breaks and proposes weighting observations to obtain optimal forecasts in the MSFE sense. We derive optimal weights for continuous and discrete break processes. Under continuous breaks, our approach recovers exponential smoothing weights. Under discrete breaks, we provide analytical expressions for the weights in models with a single regressor and asympotically for larger models. It is shown that in these cases the value of the optimal weight is the same across observations within a given regime and differs only across regimes. In practice, where information on structural breaks is uncertain a forecasting procedure based on robust weights is proposed. Monte Carlo experiments and an empirical application to the predictive power of the yield curve analyze the performance of our approach relative to other forecasting methods.
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.:
- Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996.
"Optimal changepoint tests for normal linear regression,"
Journal of Econometrics,
Elsevier, vol. 70(1), pages 9-38, January.
- Donald W.K. Andrews & Inpyo Lee & Werner Ploberger, 1992. "Optimal Changepoint Tests for Normal Linear Regression," Cowles Foundation Discussion Papers 1016, Cowles Foundation for Research in Economics, Yale University.
- M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2010.
"Variable Selection, Estimation and Inference for Multi-period Forecasting Problems,"
DNB Working Papers
250, Netherlands Central Bank, Research Department.
- Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.
- 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.
- Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
- 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.
- M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006. "Forecasting Time Series Subject to Multiple Structural Breaks," Review of Economic Studies, Oxford University Press, vol. 73(4), pages 1057-1084.
- Pesaran, M. Hashem & Pettenuzzo, Davide & Timmermann, Allan, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," IZA Discussion Papers 1196, Institute for the Study of Labor (IZA).
- Pesaran, M Hashem & Pettenuzzo, Davide & Timmermann, Allan G, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CEPR Discussion Papers 4636, C.E.P.R. Discussion Papers.
- M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CESifo Working Paper Series 1237, CESifo Group Munich.
- Giacomini, Raffaella & Rossi, Barbara, 2006.
"Detecting and predicting forecast breakdowns,"
Working Paper Series
0638, European Central Bank.
- Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
- Rossi, Barbara & Giacomini, Raffaella, 2006. "Detecting and Predicting Forecast Breakdowns," Working Papers 06-01, Duke University, Department of Economics.
- Filippo Altissimo & Valentina Corradi, 2000. "Strong Rules for Detecting the Number of Breaks in a Time Series," Econometric Society World Congress 2000 Contributed Papers 0574, Econometric Society.
- Raffaella Giacomini & Barbara Rossi, 2006.
"How Stable is the Forecasting Performance of the Yield Curve for Output Growth?,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 68(s1), pages 783-795, December.
- Rossi, Barbara & Giacomini, Raffaella, 2005. "How Stable is the Forecasting Performance of the Yield Curve for Outpot Growth?," Working Papers 05-08, Duke University, Department of Economics.
- Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
- Gary Koop & Simon M. Potter, 2007. "Estimation and Forecasting in Models with Multiple Breaks," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 763-789.
- M. Hashem Pesaran & Andreas Pick, 2011.
"Forecast Combination Across Estimation Windows,"
Journal of Business & Economic Statistics,
Taylor & Francis Journals, vol. 29(2), pages 307-318, April.
- Atsushi Inoue & Barbara Rossi, 2011. "Identifying the Sources of Instabilities in Macroeconomic Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1186-1204, November.
When requesting a correction, please mention this item's handle: RePEc:cam:camdae:1163. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jake Dyer)
If references are entirely missing, you can add them using this form.