Spatial variation as a determinant of house price: Incorporating a geographically weighted regression approach within the Belfast housing market

Abstract

Purpose

Tobler's law of geography states that things that are close to one another tend to be more alike than things that are far apart. In this regard, the spatial pattern of price distribution is defined by the arrangement of individual entities in space and the geographic relationships among them. The purpose of this paper is to provide emerging findings of research analysing the salient factors which impact on the sale price of residential properties using a spatial regression approach.

Design/methodology/approach

The research develops and formulates a geographically weighted regression (GWR) model to incorporate residential sales transactions within the Belfast Metropolitan Area over the course of 2010. Transaction data were sourced from the University of Ulster House Price Index survey (2010, Q1‐Q4). The GWR approach was then evaluated relative to a standard hedonic model to determine the spatial heterogeneity of residential property price within the Belfast Metropolitan Area.

Findings

This investigation finds that the GWR technique provides increased accuracy in predicting marginal price estimates, in comparison with traditional hedonic modelling, within the Belfast housing market.

Originality/value

This study is one of only a few investigations of spatial house price variation applying the GWR methodology within the confines of a UK housing market. In this respect it enhances applied based knowledge and understanding of geographically weighted regression.

Citation

McCord, M., Davis, P.T., Haran, M., McGreal, S. and McIlhatton, D. (2012), "Spatial variation as a determinant of house price: Incorporating a geographically weighted regression approach within the Belfast housing market", Journal of Financial Management of Property and Construction, Vol. 17 No. 1, pp. 49-72. https://doi.org/10.1108/13664381211211046