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Forecasting in the presence of recent structural change

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Author Info

  • Eklund, J.
  • Kapetanios, G.
  • Price, S.

Abstract

We examine how to forecast after a recent break. We consider monitoring for change and then combining forecasts from models that do and do not use data before the change; and robust methods, namely rolling regressions, forecast averaging over different windows and exponentially weighted moving average (EWMA) forecasting. We derive analytical results for the performance of the robust methods relative to a full-sample recursive benchmark. For a location model subject to stochastic breaks the relative MSFE ranking is EWMA

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File URL: http://openaccess.city.ac.uk/1457/1/Forecasting_in_the_presence_of_recent_structural.pdf
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Bibliographic Info

Paper provided by Department of Economics, City University London in its series Working Papers with number 11/05.

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Date of creation: 2011
Date of revision:
Handle: RePEc:cty:dpaper:11/05

Contact details of provider:
Postal: Department of Economics, Social Sciences Building, City University London, Whiskin Street, London, EC1R 0JD, United Kingdom,
Phone: +44 (0)20 7040 8500
Web page: http://www.city.ac.uk
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Related research

Keywords: monitoring; recent structural change; forecast combination; robust forecasts;

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References

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  1. Leisch, Friedrich & Hornik, Kurt & Kuan, Chung-Ming, 2000. "Monitoring Structural Changes With The Generalized Fluctuation Test," Econometric Theory, Cambridge University Press, vol. 16(06), pages 835-854, December.
  2. 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.
  3. Chu, Chia-Shang James & Stinchcombe, Maxwell & White, Halbert, 1996. "Monitoring Structural Change," Econometrica, Econometric Society, vol. 64(5), pages 1045-65, September.
  4. M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CESifo Working Paper Series 1237, CESifo Group Munich.
  5. Pesaran, M.H. & Pick, A., 2008. "Forecasting Random Walks Under Drift Instability," Cambridge Working Papers in Economics 0814, Faculty of Economics, University of Cambridge.
  6. Orbe, Susan & Ferreira, Eva & Rodriguez-Poo, Juan, 2005. "Nonparametric estimation of time varying parameters under shape restrictions," Journal of Econometrics, Elsevier, vol. 126(1), pages 53-77, May.
  7. Kapetanios, G. & Tzavalis, E., 2010. "Modeling structural breaks in economic relationships using large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 417-436, March.
  8. Kapetanios, George, 2007. "Estimating deterministically time-varying variances in regression models," Economics Letters, Elsevier, vol. 97(2), pages 97-104, November.
  9. Zeileis, Achim & Leisch, Friedrich & Kleiber, Christian & Hornik, Kurt, 2002. "Monitoring structural change in dynamic econometric models," Technical Reports 2002,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  10. Hendry, David F., 2000. "On detectable and non-detectable structural change," Structural Change and Economic Dynamics, Elsevier, vol. 11(1-2), pages 45-65, July.
  11. repec:bla:restud:v:73:y:2006:i:4:p:1057-1084 is not listed on IDEAS
  12. 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.
  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.
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Citations

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Cited by:
  1. Bailey, N. & Kapetanios, G. & Pesaran, M. H., 2012. "Exponent of Cross-sectional Dependence: Estimation and Inference," Cambridge Working Papers in Economics 1206, Faculty of Economics, University of Cambridge.
  2. Liudas Giraitis & George Kapetanios & Simon Price, 2012. "Adaptive Forecasting in the Presence of Recent and Ongoing Structural Change," Working Papers 691, Queen Mary, University of London, School of Economics and Finance.
  3. Tian, Jing & Anderson, Heather M., 2014. "Forecast combinations under structural break uncertainty," International Journal of Forecasting, Elsevier, vol. 30(1), pages 161-175.
  4. repec:cty:dpaper:12/02 is not listed on IDEAS
  5. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.

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