Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/189091 
Year of Publication: 
1988
Series/Report no.: 
Queen's Economics Department Working Paper No. 717
Publisher: 
Queen's University, Department of Economics, Kingston (Ontario)
Abstract: 
It is remarkably easy to test for structural change, of the type that the classic F or "Chow" test is designed to detect, in a manner that is robust to heteroskedasticity of possibly unknown form. This paper first discusses how to test for structural change in nonlinear regression models by using a variant of the Gauss-Newton regression. It then shows how to make these tests robust to heteroskedasticity of unknown form and discusses several related procedures for doing so. Finally, it presents the results of a number of Monte Carlo experiments designed to see how well the new tests perform in finite samples.
Subjects: 
Chow test
HCCME
heteroskedasticity
artificial regression
Gauss-Newton regression
GNR
structural break
Document Type: 
Working Paper

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