Test for Structural Change under Heteroscedastic Errors: The Case of Successive Regressions

The Chow test is not robust under heteroscedasticity. The presence of heteroscedasticity will affect level of significance as well as power of the test, especially when the sizes of the samples are small. The present paper not only resolves the problem of heteroscedasticity in the error terms, but also extends the existing method of comparing from two regression equations to many equations in order to make comparisons of the successive coefficients to be possible, thus generalizing Chow test in two directions. The procedure is then illustrated by an attempt to detect structural change, if any, through comparison of successive decadal growth rates of the population of India, using NSSO data.