Contents
Introduction. Motivating and Interpreting Spatial Econometric Models. Maximum Likelihood Estimation. Log-Determinants and Spatial Weights. Bayesian Spatial Econometric Models. Model Comparison. Spatiotemporal and Spatial Models. Spatial Econometric Interaction Models. Matrix Exponential Spatial Models. Limited Dependent Variable Spatial Models. References.

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. It explores a wide range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances.