| Abstract: | Summary In this paper we investigate the consequences of misspecification on the large sample properties of change‐point estimators and the validity of tests of the null hypothesis of linearity versus the alternative of a structural break. Specifically this paper concentrates on the interaction of structural breaks in the mean and variance of a time series when either of the two is omitted from the estimation and inference procedures. Our analysis considers the case of a break in mean under omitted‐regime‐dependent heteroscedasticity and that of a break in variance under an omitted mean shift. The large and finite sample properties of the resulting least‐squares‐based estimators are investigated and the impact of the two types of misspecification on inferences about the presence or absence of a structural break subsequently analysed. |
