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FINITE-SAMPLE PROPERTIES OF FORECASTS FROM THE STATIONARY FIRST-ORDER AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION

Published online by Cambridge University Press:  25 April 2007

Yong Bao
Yong Bao
Affiliation:
University of Texas at San Antonio
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Abstract

We study the properties of the multi-period-ahead least-squares forecast for the stationary AR(1) model under a general error distribution. We find that the forecast is unbiased up to O(T−1), where T is the in-sample size, regardless of the error distribution and that the mean squared forecast error, up to O(T−3/2), is robust against nonnormality.The author is grateful to the co-editor Paolo Paruolo and two anonymous referees for helpful comments. The author is solely responsible for any remaining errors.

Type
NOTES AND PROBLEMS
Information
Econometric Theory , Volume 23 , Issue 4 , August 2007 , pp. 767 - 773
Copyright
© 2007 Cambridge University Press

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References

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