A Comparative Perspective on Urban Spatial Housing Market Structure: Some More Evidence of Local Sub-markets Based on a Neural Network Classification of Amsterdam.

When analysing the spatial housing market structure of urban areas, a frequently arising question concerns the relevant criteria for housing market segmentation: is it the transaction price or related to other, socioeconomic. demographic and physical features of the location? In this study, two neural network techniques (SOM. LVQ, Kohonen) are used for identifying sub-markets within Amsterdam, The Netherlands. Because of the inductive nature of the modelling, any theory has to be understood in an open sense: generalising the principles of classification to another context to enable elaboration of institutionally sensitive housing market theory. These findings are therefore compared with earlier findings from another urban housing market—namely, Helsinki, Finland. The comparison shows that, while the price alone is an insufficient criterion for both markets, Amsterdam is more fragmented than Helsinki. [ABSTRACT FROM AUTHOR]