We describe the spreg command, which implements a maximum likelihood estimator and a generalized spatial two-stage least-squares estimator for the parameters of a linear cross-sectional spatial-autoregressive model with spatial-autoregressive disturbances. Copyright 2013 by StataCorp LP.

We present the spmat command for creating, managing, and storing spatial-weighting matrices, which are used to model interactions between spatial or more generally cross-sectional units. spmat can store spatial-weighting matrices in a general and banded form. We illustrate the use of the spmat...

We describe the spivreg command, which estimates the parameters of linear cross-sectional spatial-autoregressive models with spatial-autoregressive disturbances, where the model may also contain additional endogenous variables as well as exogenous variables. spivreg uses results and the...

Time series regression models that have autoregressive errors are often estimated by two-stage procedures which are based on the Cochrane-Orcutt (1949) transformation. It seems natural to also attempt the estimation of spatial regression models whose error terms are autoregressive in terms of an...