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For network effects models of network autocorrelation we use Monte Carlo methods to study the relative properties of three estimation methods. The methods are the iterative maximum likelihood estimation (Ord, 1975; Doreian, 1981), ordinary least squares, and a regression-based “quick and dirty” substitution for iterative MLE. Of the three, OLS is clearly the inferior estimation method and MLE the superior method. We recommend the use of the maximum likelihood method when network autocorrelation models are to be estimated.
Doreian et al. (Thu,) studied this question.