We identify clusters by applying techniques of model-based clustering which allow the data to inform on the nature and the number of clusters. We test the predictions of two different models one that suggests that the market will be characterised by clusters of properties with similar physical attributes, one that the market will be characterised by clusters of neighbourhoods exhibiting similar socioeconomic compositions. Rather the market may well be lumpy, being well-provided with properties exhibiting certain combinations of characteristics and sparsely provided elsewhere. That insight is that in equilibrium the market may not be characterised by a continuum of properties over attribute space. Rather than adopting progressively more flexible econometric specifications to deal with this nonlinearity we adopt an alternative estimation strategy based on a further insight provided by the theoretical literature.
Recent advances in the theoretical understanding of equilibria in property markets predict that the equilibrium hedonic price function will typically be highly nonlinear.
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