Estimating spatial models with endogenous variables, a spatial lag and spatially dependent distrurbances: Finite sample properties

This paper discusses estimation methods for models including an endogenous spatial lag, additional endogenous variables due to system feedback and an autoregressive or a moving average error process. It extends Kelejian and Prucha's, and Fingleton and Le Gallo's feasible generalized spatial two-stage least squares estimators and also considers HAC estimation in a spatial framework as suggested by Kelejian and Prucha. An empirical example using real estate data illustrating the different estimators is proposed. The finite sample properties of the estimators are finally investigated by means of Monte Carlo simulation.