Model Instability and Choice of Observation Window in Autoregressive Models∗
نویسندگان
چکیده
Recent evidence suggests that many economic time series are subject to structural breaks, yet little is known about the properties of alternative forecasting methods for such data. This paper proposes a new method for determining the window size that explores the trade-off between bias and forecast error variance to minimize the mean squared forecast error in the presence of breaks in autoregressive models. An application to output growth in the OECD compares the performance of the proposed method to that of several existing approaches to forecasting under model instability. JEL Classifications: C22, C53.
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