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A Model of Spatial Patterns across Local Retail Property Markets in Great Britain

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  • Catherine Jackson

    (Centrefor Property Research, Department of Land Economy, University of Aberdeen, Elphinstone Road, Aberdeen, AB24 3UF, UK, c.c.jackson@abdn.ac.uk)

Abstract

Property markets are commonly modelled either at relatively high levels of aggregation (such as regional or national) using time-series data or panel data, or at individual-town level. This paper develops a cross-sectional model of a large number of retail property markets at the city and town level. The model is developed using prime retail rental levels data as the dependent variable and a number of demand and supply variables, suggested by theory, as independent variables. The model takes the form of a single equation and is based on multiple linear least-squares regression analysis. During the course of the paper, a number of issues are addressed: principal components analysis is suggested as a method of reducing multicollinearity in a model, and the spatial stability of the model is assessed. The paper concludes that the size of the retail core (as measured by the number of national multiple retailers present) and the demographic profile of the local population provide a highly significant explanation for the differential rental levels across towns and cities in Great Britain. The model generally exhibits a high degree of spatial stability, when tested using dummy variables and F tests. However, there is some evidence of spatial instability in the common model between southern and northern centres, large versus smaller centres and across centres with high, medium or low rental levels, but this is inconclusive.

Suggested Citation

  • Catherine Jackson, 2001. "A Model of Spatial Patterns across Local Retail Property Markets in Great Britain," Urban Studies, Urban Studies Journal Limited, vol. 38(9), pages 1445-1471, August.
    • Handle: RePEc:sae:urbstu:v:38:y:2001:i:9:p:1445-1471
    DOI: 10.1080/00420980120076740
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    References listed on IDEAS

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