Spatial variation as a determinant of house price

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.

Spatial heterogeneity in implicit housing prices: evidence from Hangzhou, China

“…Several hedonic studies emphasize the appealing empirical performance of GWR. As expected, Saefuddin and Yekti (2012), Hanink et al (2012) and McCord et al (2012) reported a better GWR performance compared to OLS. Kestens et al (2006) and Bitter et al (2007) measured GWR against the spatial expansion model, and verified that the GWR model outperforms the spatial expansion model in terms of explanatory power and predictive accuracy.…”

Impact of a Vicinity of Airport on the Prices of Single-Family Houses with the Use of Geospatial Analysis

“…In interesting paper of [26] a GWR model is established to explore spatially varying relationships between house price and floor area with sampled house prices in London. It can be stated that in recent years, there has been an increasing interest in the application of geographically weighted regression on housing market for example in research of [27][28][29][30][31].…”

Towards Increasing Residential Market Transparency: Mapping Local Housing Prices and Dynamics

“…Prices and values of real estate depend on many exogenous and endogenous elements, which should be taken into account in the market analysis, with a particular emphasis on detailed location [25][26][27][28]. One of the essential elements of such an analysis is to isolate the impact of location factors that constitute the essence of cartographic reflection of value [29]. Considerations on location in the context of determining the determinants of apartment prices are presented, among others, by Kiel and Zabel [30] and Kolbe et al [31], indicating at the same time relatively simple methods of econometric modelling as a primary tool for identifying location factors.…”