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THE APPROXIMATE MOMENTS OF THE LEAST SQUARES ESTIMATOR FOR THE STATIONARY AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION

Published online by Cambridge University Press:  14 May 2007

Yong Bao
Yong Bao
Affiliation:
Temple University
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Abstract

I derive the approximate bias and mean squared error of the least squares estimator of the autoregressive coefficient in a stationary first-order dynamic regression model, with or without an intercept, under a general error distribution. It is shown that the effects of nonnormality on the approximate moments of the least squares estimator come into play through the skewness and kurtosis coefficients of the nonnormal error distribution.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 5 , October 2007 , pp. 1013 - 1021
Copyright
© 2007 Cambridge University Press

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