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Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks

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dc.contributor.authorPesaran, M. Hashem
dc.contributor.authorTimmermann, Allan
dc.date.accessioned2004-06-16T16:05:31Z
dc.date.available2004-06-16T16:05:31Z
dc.date.created2003-06en_GB
dc.date.issued2004-06-16T16:05:31Z
dc.description.abstractAutoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural breaks. This paper develops a theoretical framework for the analysis of small-sample properties of forecasts from general autoregressive models under a structural break. Our approach is quite general and allows for unit roots both pre- and post-break. We derive finite-sample results for the mean squared forecast error of one-step-ahead forecasts, both conditionally and unconditionally and present numerical results for different types of break specifications. Implication of breaks for the determination of the optimal window size are also discussed.
dc.format.extent311701 bytes
dc.format.mimetypeapplication/pdfen_GB
dc.format.mimetypeapplication/pdf
dc.identifier.doi10.17863/CAM.5119
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/363
dc.language.isoeng
dc.publisherFaculty of Economics
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserved
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.subject.classificationClassification-JEL: C33, C5
dc.subject.othersmall sample properties of forecasts, RMSFE, structural breaks, autoregression
dc.titleSmall Sample Properties of Forecasts from Autoregressive Models under Structural Breaks
dc.typeWorking Paper
rioxxterms.versionAO

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