BIASES OF ESTIMATORS IN MULTIVARIATE NON‐GAUSSIAN AUTOREGRESSIONS
- 1 May 1990
- journal article
- Published by Wiley in Journal of Time Series Analysis
- Vol. 11 (3) , 249-258
- https://doi.org/10.1111/j.1467-9892.1990.tb00056.x
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.Keywords
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