We consider the finite sample power of various tests against serial correlation in the disturbances of a linear regression when these disturbances follow a stationary long memory process. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin-Watson test and many other tests that can be written as ratios of quadratic forms in the disturbances, the power can drop to zero for certain regressors. We also provide a means to detect this zero-power trap. Our results depend solely on the correlation structure and allow for fairly arbitrary nonlinearities.
Durbin-Watson test power autocorrelation long memory