This paper explores the properties of pre-test strategies in estimating a linear Cliff–Ord-type spatial model when the researcher is unsure about the nature of the spatial dependence. More specifically, the paper explores the finite sample properties of the pre-test estimators introduced in...

This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as...

Various two stage least squares procedures have been suggested for the estimation of the autoregressive parameter in the spatial autoregressive model of order one. These procedures are computationally convenient and so their use is "tempting". In this paper we show that these procedures are, in...

Cross sectional spatial models frequently contain a spatial lag of the dependent variable as a regressor, or a disturbance term which is spatially autoregressive. In this paper we describe a computationally simple procedure for estimating cross sectional models which contain both of these...