Author:
Julia Bondarenko
Affiliation:
Helmut-Schmidt University Hamburg, University of the Federal Armed Forces Hamburg, Germany
Keyword(s):
CUSUM test for structural breaks, recursive residuals, power of test, mixture distribution, Monte Carlo simulation.
Related
Ontology
Subjects/Areas/Topics:
Business Analytics
;
Change Detection
;
Data Engineering
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Structural shifts in time series can occur as consequences of complex processes, arising in system. An ignorance of such structural changes can cause an associated regression model misspecification. In practice, early detection and response to outbreaks, causing the changes in a process, is highly important. The famous CUSUM test of Brown, Durbin & Evans, has a poor power in detecting the structural breaks in parameters occurring early (and also late) in the sample. In this paper, we propose CUSUM-similar test which, due to the transformation of recursive residuals forces the detection of temporal dependence structure in linear regression model and has a larger power for the early structural breaks. Here our interest centres on the detection of single breaks occurring in parameters of the linear model. Distribution and other probabilistic characteristics of the transformed residuals are provided, the boundaries for the new test are derived. The new test can be considered then as a co
mplement to the standard CUSUM test.
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