Robustness and Size of Tests of Autocorrelation and Heteroscedasticity to Non-Normality

A comprehensive empirical examination is made of the sensitivity of tests of disturbance covariance in the linear regression model to non-normal disturbance behaviour. Tests of autocorrelation appear to be quite robust, except for extreme non-normality, but tests for heteroscedasticity are highly susceptible to kurtosis.