The selection of the order and identification of nonzero elements in the polynomial matrices of vector autoregressive processes

Abstract

In this paper we show how the residual white noise autoregressive order selection procedure can be used not only to effectively identify the order of Vector Autoregressive (VAR) processes, but also with the use of a seemingly-unrelated-type of estimation method to identify nonzero elements in the polynomial matrices of VAR models. Results from extensive simulation studies as well as from economic data are presented to demonstrate the performance of the proposed method.

Keywords:

• Autoregressions
• order determination criteria
• parameter constraints
• Grangercausality