This paper reviews a number of conceptual issues pertaining to the implementation of an explicit "spatial" perspective in applied econometrics. It provides an overview of the motivation for including spatial effects in regression models, both from a theory-driven as well as from a data-driven...

This paper investigates the asymptotic properties of the ordinary least squares estimator for spatial autoregressive models. We show that this estimator is biased as well as inconsistent for the parameters regardless of the distribution of the error term. Illustrative examples are also provided.

This article discusses and applies an information-theoretic framework for incorporating knowledge of the spatial structure in a sample while extracting from it information about processes resulting in count outcomes. The framework, an application of the Generalized Cross-Entropy (GCE) method of...

Random fields are stochastic processes indexed by a multidimensional parameter. They possess some interesting properties, e.g. isotropy and the Markov property, and satisfy laws of large numbers and weak convergence theorems under fairly general conditions. As such, random fields provide a...