In this paper we propose a Structural Equation Model (SEM) approach with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spill-over effects, of which the observed spatially lagged variables are indicators. This approach allows to incorporate and test more information on spatial dependence and offers more flexibility than the representation in terms of Wy or Wx. Furthermore, we adapt the estimators included in the software packages Mx and LISREL 8 to estimate SEMs with spatial dependence. We present an illustration based on Anselin’s (1988) Columbus, Ohio, crime data set.