In this paper the problems of specification and nonnested model comparison in spatial and network econometrics are examined, and the Bayesian posterior probabilities approach is developed. The theory is developed for the comparison of alternative spatial weights matrices in both the systematic and the disturbance components of models, and also for the comparison of alternative spatial disturbance processes. Several empirical illustrations are provided, and extensions of the Bayesian approach are discussed.
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