Neglecting Parameter Changes in Autoregressive Models
نویسنده
چکیده
We study situations in which autoregressive models are estimated on time series that contain switches in the data generating parameters and these switches are not accounted for. The geometry of this estimation problem causes estimated vector autoregressive models to display a unit eigenvalue, and the sum of the estimated autoregressive parameters of ARMA and GARCH models to be close to one. This artefact is a confounding factor in the analysis of persistence. If the existence of parameter changes in a time series cannot be ruled out, autoregressive models are an inadequate research tool to capture the dynamics of the series. Data must be analyzed for possible change-points before the sample period for an autoregressive model can be specified. JEL codes: C22, C51
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