BIASES OF ESTIMATORS IN MULTIVARIATE NON‐GAUSSIAN AUTOREGRESSIONS

Alun Lloyd Pope

Journal of Time Series Analysis, 1990, vol. 11, issue 3, 249-258

Abstract: Abstract. Expressions for the bias of the least‐squares and modified Yule‐Walker estimators in a correctly specified multivariate autoregression of arbitrary order are obtained without assuming that the innovations are Gaussian. Instead, the innovations are assumed to form a martingale difference sequence which is stationary up to sixth order and which has finite sixth moments. The errors in the expressions are shown to be O(n‐3/2), as the sample size n under some moment conditions. The expressions obtained are the same in the Gaussian and non‐Gaussian cases.

Date: 1990
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