Spatial modelling of economic phenomena (growth, unemployment, location, house prices, crime rates and so on) requires the adoption of complex econometric tools, which allow us to deal with some important methodological issues, such as spatial dependence, spatial heterogeneity and nonlinearities. In this paper we discuss some recent contributions to the spatial econometrics literature, which have provided instruments (such as Spatial Autoregressive Semiparametric Geoadditive Models), which address these issues simulta-neously. We also present an application of these methods to the case of housing prices in Lucas County.