On Testing Changes in Autoregressive Parameters of a VAR Model

Marek Dvořák · Zuzana Prášková

8 citations0/0 files storedCommunication in Statistics- Theory and Methods

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Monetary Policy and Economic Impact Advanced Statistical Methods and Models Statistical and numerical algorithms

Abstract

The article deals with the problem of testing a change in autoregressive matrices of the p-th order vector autoregressive process, VAR(p). The proposed test statistics are based on the likelihood ratio concept and are studied under the null hypothesis of no change in parameters. Their asymptotic behavior is derived under minimal moment assumptions in both cases where the time point of possible change is known a priori and is undefined. The Gumbel-type approximation of the test statistic is also developed, which previous papers on VAR(p) models do not cover.

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References

1993Tests for Parameter Instability and Structural Change With Unknown Change Point 2010Analysis of Financial Time Series 1998Testing For and Dating Common Breaks in Multivariate Time Series 2000Change-Point Estimation in ARCH Models 1987Tests for a Change-Point 1993The Maximum Likelihood Method for Testing Changes in the Parameters of Normal Observations 1995Testing for a Change in the Parameter Values and Order of an Autoregressive Model 2006On the detection of changes in autoregressive time series I. Asymptotics

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