Robust heteroskedasticity-robust tests

•Robustness of Hausman and Palmer's heteroscedasticity-robust test is investigated.•It is found to have large size distortion in several data generating processes.•A wild bootstrap test has much better size in finite samples.•Hausman and Palmer provides no robust power improvement over the wild bootstrap.

Hausman and Palmer (2012) suggest using the Edgeworth corrected critical values of Rothenberg (1988) along with a pairs bootstrap covariance matrix estimator in order to obtain second order correct heteroskedasticity-robust inferences. According to their simulations, this test has size comparable to and power greater than a wild bootstrap test. In this note, I show that this does not hold in general. Using a more extensive set of simulations reveals that the wild bootstrap test is much more robust to the underlying data generating process.