In a Monte Carlo experiment we show that using a small probability of Type I error may lead to reduced pretest estimator MSE when a Hausman pretest is used to choose between least squares and instrumental variables estimators.

Often, authors report materially different OLS and spatial error model estimates. However, under the null of correct specification, these estimates should be similar. We propose a spatial Hausman test and conduct a Monte Carlo experiment to examine its performance.