Test of heteroscedasticity in a regression model in the presence of measurement errors

This study investigates the behaviour of test statistics for heteroscedasticity of the disturbances in a simple regression model when the regressor is measured with error. By means of simulation, the performance of the test statistics are studied when applied to least squares residuals and residuals obtained from instrumental variables estimation. The results show that the least squares residuals could be used for diagnostic checking even if the estimation method is based on instrumental variables. We also found that great care has to be taken when applying the frequently used White test.