The number of studies investigating neighbourhood effects has increased rapidly over the last two decades. Although many of these studies claim to have found evidence for neighbourhood effects, most 'evidence' is likely the result of reversed causality. The main challenge in modelling neighbourhood effects is the (econometric) identification of causal effects. The most severe problem is selection bias as a result of selective sorting into neighbourhoods. This paper argues that in order to further our understanding of neighbourhood effects we should explicitly incorporate neighbourhood sorting into our models. Neighbourhood effect studies are in the situation where the processes behind one of its key methodological problems (selection bias) are also critical to fully understand the neighbourhood context itself. It is thus remarkable that residential mobility and neighbourhood sorting has been almost completely ignored in the neighbourhood effects literature.