Before revision:  The choice among different estimators also affect the relevance of spatial correlation for inference  . Simulations with real datasets corroborate these conclusions.
After revision:  The choice among different estimators also affect the relevance of spatial correlation for inference (when it is ignored) depends on the amount of spatial correlation that remains after we control for the time- and group-invariant unobservables. As a consequence, details such as the time frame used in the estimation, and the choice of the estimator, will be key determinants on the degree of distortions we should expect when spatial correlation is ignored . Simulations with real datasets corroborate these conclusions.