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Adaptive Forcasting in the Presence of Recent and Ongoing Structural Change

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  • Liudas Giraitis

    ()

  • George Kapetanios

    ()

  • Simon Price

    ()

Abstract

We consider time series forecasting in the presence of ongoing structural change where both the time series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially weighted moving averages, known to be robust to historical structural change, are found to be also useful in the presence of ongoing structural change in the forecast period. A crucial issue is how to select the degree of downweighting, usually defined by an arbitrary tuning parameter. We make this choice data dependent by minimizing forecast mean square error, and provide a detailed theoretical analysis of our proposal. Monte Carlo results illustrate the methods. We examine their performance on 191 UK and US macro series. Forecasts using data-based tuning of the data discount rate are shown to perform well.

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Bibliographic Info

Paper provided by Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University in its series CAMA Working Papers with number 2012-14.

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Length: 48 pages
Date of creation: Mar 2012
Date of revision:
Handle: RePEc:een:camaaa:2012-14

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References

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  1. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche, Centre interuniversitaire de recherche en économie quantitative, CIREQ 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  2. George Kapetanios & Vincent Labhard & Simon Price, 2006. "Forecasting Using Predictive Likelihood Model Averaging," Working Papers, Queen Mary, University of London, School of Economics and Finance 567, Queen Mary, University of London, School of Economics and Finance.
  3. Rodríguez Poo, Juan M. & Ferreira García, María Eva & Orbe Mandaluniz, Susan, 2001. "Nonparametric estimation of time varying parameters under shape restrictions," BILTOKI, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) 2001-02, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
  4. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521634809.
  5. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, Elsevier, vol. 137(1), pages 134-161, March.
  6. Jennifer Castle & David Hendry & Nicholas W.P. Fawcett, 2011. "Forecasting breaks and forecasting during breaks," Economics Series Working Papers, University of Oxford, Department of Economics 535, University of Oxford, Department of Economics.
  7. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 14(1), pages 11-30, January.
  8. Hendry, David F., 2000. "On detectable and non-detectable structural change," Structural Change and Economic Dynamics, Elsevier, Elsevier, vol. 11(1-2), pages 45-65, July.
  9. Eklund, J. & Kapetanios, G. & Price, S., 2011. "Forecasting in the presence of recent structural change," Working Papers, Department of Economics, City University London 11/05, Department of Economics, City University London.
  10. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 943, Cowles Foundation for Research in Economics, Yale University.
  11. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier, Elsevier.
  12. Kapetanios, George, 2007. "Estimating deterministically time-varying variances in regression models," Economics Letters, Elsevier, Elsevier, vol. 97(2), pages 97-104, November.
  13. Elliott, Graham & Timmermann, Allan G, 2007. "Economic Forecasting," CEPR Discussion Papers, C.E.P.R. Discussion Papers 6158, C.E.P.R. Discussion Papers.
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Cited by:
  1. Jungmittag, Andre, 2014. "Combination of forecasts across estimation windows: An application to air travel demand," Working Paper Series: Business and Law, Frankfurt University of Applied Sciences, Faculty of Business and Law 05, Frankfurt University of Applied Sciences, Faculty of Business and Law.
  2. Giraitis, Liudas & Kapetanios, George & Theodoridis, Konstantinos & Yates, Tony, 2014. "Estimating time-varying DSGE models using minimum distance methods," Bank of England working papers, Bank of England 507, Bank of England.

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