Residential property value and locational externalities: on the complementarity and substitutability of approaches
||Residential property value and locational externalities: on the complementarity and substitutability of approaches
||8th European Real Estate Society Conference (26-29 June 2001) Alicante, Spain
||It is well-known from the literature that the location affects price formation of residential property. Location specific externalities can increase or reduce the value compared to a similar house situated elsewhere. The price effect of the location is usually studied empirically with the hedonic price models, by including various neighbourhood and proximity variables in the model. These regression based techniques have, however, been criticised for a number of reasons. The arguments pertain partly to technical issues such as model flexibility, functional discontinuity and nonlinearity, and data quality, and partly to more fundamental problems related to the essential nature of the value formation process. The criticism has attracted researchers to experiment with new approaches, each of which could add something substantial to the standard hedonic approach. Given an ample modelling repertoire, the question is, whether various methods are ‘real alternatives’ or mere ‘extension parts’ to one another? The paper highlights the rationale behind each broad approach composed of specific modelling techniques currently available. An extremely mechanical approach does not appeal to everyone, even though scale benefits are achieved. On the other hand, a totally problem centric and context specific method may turn too dependent on assumptions and therefore exhibit invalid conclusions. The case is demonstrated by applying two fairly new approaches to locational value determination: the self-organising map (SOM, a type of neural network) and the analytic hierarchy process (AHP, a type of value tree). Both approaches have their contributions: the SOM unveils patterns among a complex data set whereas the AHP enables quantification of qualitative judgments. The SOM-based method uses actual market data and as such represents a more sophisticated variant of hedonic regression modelling. The AHP-based method in turn is fundamentally different as it primarily deals with perceptions and preferences of experts, and may lead to conclusions that go beyond the purely economic value framework (if such a problem setting is preferred).
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||The role of the location
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