Abstract
This paper reviews tests for structural change in linear regression models from the generalized fluctuation test framework as well as from the F test (Chow test) framework. It introduces a unified approach for implementing these tests and presents how these ideas have been realized in an R package called strucchange. Enhancing the standard significance test approach the package contains methods to fit, plot and test empirical fluctuation processes (like CUSUM, MOSUM and estimates-based processes) and to compute, plot and test sequences of F statistics with the supF , aveF and expF test. Thus, it makes powerful tools available to display information about structural changes in regression relationships and to assess their significance. Furthermore, it is described how incoming data can be monitored.
Highlights
The problem of detecting structural changes in linear regression relationships has been an important topic in statistical and econometric research
The most important classes of tests on structural change are the tests from the generalized fluctuation test framework (Kuan and Hornik 1995) on the one hand and tests based on F statistics (Hansen 1992a; Andrews 1993; Andrews and Ploberger 1994) on the other
Is that the change point has to be known in advance, but there are tests based upon F statistics (Chow statistics), that do not require a specification of a particular change point and which will be introduced
Summary
The problem of detecting structural changes in linear regression relationships has been an important topic in statistical and econometric research. The most important classes of tests on structural change are the tests from the generalized fluctuation test framework (Kuan and Hornik 1995) on the one hand and tests based on F statistics (Hansen 1992a; Andrews 1993; Andrews and Ploberger 1994) on the other. This paper concerns ideas and methods for implementing generalized fluctuation tests as well as F tests in a comprehensive and flexible way, that reflects the common features of the testing procedures.
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