On testing for nonlinearity in multivariate time series

被引：2
|
作者：
Psaradakis, Zacharias [1 ]
Vavra, Marian [2 ]
机构：
[1] Univ London, Dept Econ Math & Stat, London WC1E 7HU, England
[2] Natl Bank Slovakia, Res Dept, Bratislava, Slovakia
来源：
ECONOMICS LETTERS | 2014年 / 125卷 / 01期
关键词：
Multivariate time series; Nonlinearity tests; Principal components;
D O I：
10.1016/j.econlet.2014.07.031
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This paper considers a multivariate extension of the test for neglected nonlinearity proposed by Tsay (1986) that uses principal components to overcome the problem of dimensionality that is common with tests of this type. Monte Carlo experiments reveal that the modified multivariate test provides a significant dimensional reduction without suffering from any systematic level distortion or power loss, and is more powerful than univariate nonlinearity tests. (C) 2014 Elsevier B.V. All rights reserved.
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页码：1 / 4
页数：4
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