Properties of Predictors in Misspecified Autoregressive Time Series Models
- 1 December 1985
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 80 (392) , 941
- https://doi.org/10.2307/2288558
Abstract
This article investigates major effects of misspecification in stationary linear time series models when we fit a pth-order autoregressive model. The true model can be an autoregressive moving average model. We derive the formulas of bias and mean squared error (MSE) of the least squares estimator and the hth period ahead prediction MSE in the time domain. Contrary to previous studies, the process in estimation is not necessarily independent of the process in prediction, and the distribution of process is not necessarily Gaussian. We examine the effects of this dependence and nonnormality on prediction in misspecified models.Keywords
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