The potential for spatial dependence in models of voter turnout, although plausible from a theoretical perspective, has not been adequately addressed in the literature. Using recent advances in Bayesian computation, the authors formulate and estimate the previously unutilized spatial Durbin...

LeSage and Pace (2009) consider the impact of omitted variables in the face of spatial dependence in the disturbance process of a linear regression relationship. Remarkably, they show that this can lead to a spatial regression model specification containing a spatial lag of the dependent and...

This tutorial is designed to introduce readers to Bayesian variants of the standard SAR and SEM models that are the most widely used and applied models in spatial econometrics. Particular attention is paid to the mathematical derivations required to obtain the full conditional distributions...