Estimation in a first order autoregressive scheme with non—normal stable disturbances

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Abstract
This paper considers the estimation of the first—order autoregressive scheme when the underlying distribution is non—normal stable. The results of a simulation experiment of the least—squares estimator and the uncorrected and corrected serial correlation coefficients are presented. It is found that, in general, normal theory results are inapplicable. Nevertheless, the corrected coefficient provides a reliable and very efficient estimator of ρ; however, the least—squares estimator and the uncorrected coefficient are severely biased with skewed populations. Furthermore, all of the estimators seem to be asymptotically non—normal.

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