In recent years, land value capture has attracted increasing attention because of its potential for funding transport infrastructure. It is well acknowledged that transport infrastructure can improve accessibility to employment and amenities; thus one might expect that it is the improved accessibility that adds value to land. Therefore, the issues in the relationship between transport accessibility and land value rise in connection with the concept of land value capture. A study looked at the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR). Traditional techniques, such as hedonic models, used to understand the attributes of land value, are global models that could be misleading in examining the spatially varying relationships, such as transport accessibility and land value. By using the Tyne and Wear region in the United Kingdom as a case study, the study revealed that nonstationarity existing in the relationship between transport accessibility and land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others; this suggests that a uniform land value capture would be inappropriate. The use of GWR allows such spatially varying relationships to be revealed, leading to a better understanding of the factors determining positive land value uplift and the implications of spatially dependent transport access premiums in housing values in the context of value capture policies.


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    Titel :

    Relationship between Transport Accessibility and Land Value


    Untertitel :

    Local Model Approach with Geographically Weighted Regression


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Du, Hongbo (Autor:in) / Mulley, Corinne (Autor:in)


    Erscheinungsdatum :

    01.01.2006




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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