DETERMINING THE ORDER OF A VECTOR AUTOREGRESSION WHEN THE NUMBER OF COMPONENT SERIES IS LARGE

Sergio G. Koreisha and Tarmo Pukkila

Journal of Time Series Analysis, 1993, vol. 14, issue 1, 47-69

Abstract: Abstract. We contrast the performance of several methods used for identifying the order of vector autoregressive (VAR) processes when the number K of component series is large. Through simulation experiments we show that their performance is dependent on K, the number of nonzero elements in the polynomial matrices of the VAR parameters and the permitted upper limit of the order used in testing the autoregressive structure. In addition we introduce a new quite powerful multivariate order determination criterion.

Date: 1993
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https://doi.org/10.1111/j.1467-9892.1993.tb00129.x

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