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

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  • Tom Kauko

    (OTB Research Institute for Housing, Urban and Mobility Studies, Jaffalaare 9, Postbus 5030, NL-2600 GA Delft, The Netherlands, Kauko@otb.tudelft.nl)

Abstract

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.

Suggested Citation

  • Tom Kauko, 2004. "A Comparative Perspective on Urban Spatial Housing Market Structure: Some More Evidence of Local Sub-markets Based on a Neural Network Classification of Amsterdam," Urban Studies, Urban Studies Journal Limited, vol. 41(13), pages 2555-2579, December.
    • Handle: RePEc:sae:urbstu:v:41:y:2004:i:13:p:2555-2579
    DOI: 10.1080/0042098042000294565
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    References listed on IDEAS

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    2. Olumayokun Soremekun & Charles A. Malgwi, 2013. "Exploring Patterns in ICT Growth and Development in Africa: A Kohonen Map Analysis," The Review of Regional Studies, Southern Regional Science Association, vol. 43(2,3), pages 175-190, Winter.

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