The paper develops an asymptotically valid F -test that is robust to spatial autocorrelation in a GMM framework. The validity of the F -test is established under mild conditions that can accommodate a wide range of spatial processes. The proposed F -test is very easy to implement, as critical values are from a standard F -distribution. The F -test achieves triple robustness: it is asymptotically valid regardless of the spatial autocorrelation, the sampling region, and the limiting behavior of the smoothing parameter. Simulation also shows that the F -test has good size and power properties in finite samples.