Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks

Allan Timmermann and Mohammad Pesaran

No 990, CESifo Working Paper Series from CESifo

Abstract: Autoregressive 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. Implications of breaks for the determination of the optimal window size are also discussed.

Keywords: small sample properties of forecasts; RMSFE; structural breaks; autoregression (search for similar items in EconPapers)
Date: 2003
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo_wp990.pdf (application/pdf)

Related works:
Journal Article: Small sample properties of forecasts from autoregressive models under structural breaks (2005)
Working Paper: Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks (2004)
Working Paper: Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks (2003)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_990

Access Statistics for this paper

More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC.
Bibliographic data for series maintained by Klaus Wohlrabe ().