Spatial econometric methods help account for the lack of independence between geographical observations and the differentiation of variables in space. These techniques have become more common in studies using geographical data. This article focuses on incorporating spatial autocorrelation and spatial heterogeneity into regression relationships. The researchers present estimation and inference procedures for models that include these effects. The first part of the article discusses spatial autocorrelation, while this second part focuses on spatial heterogeneity.