Adaptive Forcasting in the Presence of Recent and Ongoing Structural Change
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.
|Date of creation:||Mar 2012|
|Date of revision:|
|Contact details of provider:|| Postal: Crawford Building, Lennox Crossing, Building #132, Canberra ACT 2601|
Phone: +61 2 6125 4705
Fax: +61 2 6125 5448
Web page: http://cama.crawford.anu.edu.au
More information through EDIRC
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.:
- Clements,Michael & Hendry,David, 1998.
"Forecasting Economic Time Series,"
Cambridge University Press, number 9780521634809, November.
- Eklund, Jana & Kapetanios, George & Price, Simon, 2010.
"Forecasting in the presence of recent structural change,"
Bank of England working papers
406, Bank of England.
- Jana Eklund & George Kapetanios & Simon Price, 2011. "Forecasting in the presence of recent structural change," CAMA Working Papers 2011-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Eklund, J. & Kapetanios, G. & Price, S., 2011. "Forecasting in the presence of recent structural change," Working Papers 11/05, Department of Economics, City University London.
- Donald W.K. Andrews, 1990.
"Tests for Parameter Instability and Structural Change with Unknown Change Point,"
Cowles Foundation Discussion Papers
943, Cowles Foundation for Research in Economics, Yale University.
- Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
- Clements, Michael P & Hendry, David F, 1996. "Intercept Corrections and Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 475-94, Sept.-Oct.
- Rodríguez Poo, Juan M. & Ferreira García, María Eva & Orbe Mandaluniz, Susan, 2001.
"Nonparametric estimation of time varying parameters under shape restrictions,"
2001-02, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
- 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.
- 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.
- 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.
- Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
- Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
- James H. Stock & Mark W. Watson, 1994.
"Evidence on structural instability in macroeconomic times series relations,"
Working Paper Series, Macroeconomic Issues
94-13, Federal Reserve Bank of Chicago.
- 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.
- James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
- Kapetanios, George, 2007. "Estimating deterministically time-varying variances in regression models," Economics Letters, Elsevier, vol. 97(2), pages 97-104, November.
- George Kapetanios & Vincent Labhard & Simon Price, 2006.
"Forecasting Using Predictive Likelihood Model Averaging,"
567, Queen Mary University of London, School of Economics and Finance.
- Kapetanios, George & Labhard, Vincent & Price, Simon, 2006. "Forecasting using predictive likelihood model averaging," Economics Letters, Elsevier, vol. 91(3), pages 373-379, June.
- Elliott, Graham & Timmermann, Allan G, 2007.
CEPR Discussion Papers
6158, C.E.P.R. Discussion Papers.
- Jennifer Castle & David Hendry & Nicholas W.P. Fawcett, 2011. "Forecasting breaks and forecasting during breaks," Economics Series Working Papers 535, University of Oxford, Department of Economics.
- 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.
- Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
When requesting a correction, please mention this item's handle: RePEc:een:camaaa:2012-14. 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: (Cama Admin)
If references are entirely missing, you can add them using this form.