Biases of estimators in multivariate non-Gaussian autoregressions

Alun Lloyd Pope

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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.

Original languageEnglish
Pages (from-to)249-258
Number of pages10
JournalJournal of Time Series Analysis
Issue number3
Publication statusPublished - 1 Jan 1990
Externally publishedYes


  • Autoregressive models
  • bias
  • least‐squares estimation
  • modified Yule‐Walker estimation

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