Properties of Tests for Spatial Error Components∗

In spatial econometrics, the typical alternative of spatial autocorrelation is expressed in the form of a spatial autorregressive process. While the bulk of the literature is devoted to specification tests and estimation methods for this model, alternatives have been suggested as well. In this paper, we consider an alternative that takes the form of the spatial error components formulation proposed by Kelejian and Robinson (1995). We consider a number of specification tests against this alternative, based on both a maximum likelihood framework as well as on a general method of moments estimation approach. We compare the performance of these tests in a series of Monte Carlo simulation experiments for a range of different spatial layouts and under a number of different error distributions.