Citation
Cheruiyot, K. (2024), "Editorial", International Journal of Housing Markets and Analysis, Vol. 17 No. 6, pp. 1349-1350. https://doi.org/10.1108/IJHMA-11-2024-190
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited
As guest editor, I welcome you to the International Journal of Housing Markets and Analysis special edition on Spatial Analysis and Housing Markets. As evident by the trends in social sciences toward spatial analyses, this special edition focuses on a relevant, but a research issue that has received little attention in housing market research. This is despite the fact that residential real estate is location specific; meaning there is adequate motivation to understand such problems from relevant spatial scales, such as regions, zones, neighborhoods or specific sites. The analyses that go beyond traditional analyses to incorporate spatial analyses provide complete perspective to guide decision-making. This is now possible due to the help of advanced computational technology and availability of geocoded data. I hope that this volume will be of an interest to real estate researchers on spatial analysis of housing markets in particular and real estate markets in general. As guest editor, I would like to thank the authors and referees for their contribution to this special issue.
The six papers in this special edition include cutting-edge research and unique data analysis approaches from a diverse range of countries and varying continents. I offer a glance of what these papers offer to the readers.
At a broader spatial scale, the paper by Akinsomi, Bangura and Yacim investigates the effect of mining activities on house prices in South Africa’s mining and non-mining towns. The authors deployed an auto-regressive distributed lag model and found that both changes in mining activities and inflationary pressure impact the housing price of mining towns directly and instantaneously in the short run. The paper further found that increasing housing supply will help cushion house prices in both mining and non-mining submarkets. However, the paper found evidence of one-way spillover in housing prices from mining towns to non-mining towns and none in return. In the long run, a favorable mortgage lending rate and adequate housing supply are beneficial.
The paper by Rajaei, Mottaghi, Sahar and Bahadori investigates the spatial distribution of housing prices and the influencing factors on the cost of residential units in the metropolis of Tehran, Iraq. The authors employ ordinary least squares (OLS) regression and geographically weighted regression (GWR) to model the data. Based on the results, the GWR performed better than the OLS regression in modeling housing prices in the study area. The GWR results show that access to sports fields, distance from gas stations and distance from water stations emerged with statistically significant results. The distance from fault has an insignificant impact on increasing housing prices at the city level. These results indicate that the housing prices in Tehran are affected by the access level to urban services and facilities, supporting the need for the Tehran metro and other stakeholders to focus their efforts on fostering sustainable housing.
Salov’s paper explores the dynamics of house prices and sales in spatial and temporal dimensions across British regions. The price diffusion model, proposed by Holly et al. (2011), was applied to the UK house price index data set, while a bivariate global vector autoregression (GVAR) model without a time trend was applied to house prices and transaction volumes retrieved from the nationwide building society. The price diffusion model, which incorporated spatial and temporal dimensions, demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in non-dominant regions with a delay. The GVAR model, based on the generalized impulse response functions framework, found some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. These results contribute to the betterment in understanding how house price changes move across regions and time within a UK context.
Cheruiyot, Mavundla, Siteleki and Lengaram’s paper examines the relationship between Cell Phone Tower Base Stations (CPTBSs) and residential property prices within the City of Johannesburg, South Africa. They employ a semi-log hedonic pricing model to test the hypothesis that the proximity of CPTBSs to residential properties does not account for any variation in residential property prices. The paper’s results show a significant impact that the proximity of CPTBS has on residential property sale prices. However, the impact of CTPBSs’ proximity on residential property prices depends on their distance from the residential properties. The closer a residential property is to the CTPBS, the greater the impact that the CTPBS will have on the selling price of the residential property. The paper adds to the limited research on the effects of CTPBSs in South Africa, offering a nuanced understanding to various stakeholders, including real estate practitioners, property owners, telecommunications companies and the public.
Wang, Lin and Tan explore the drivers of housing affordability using the post-least absolute shrinkage and selection operator (LASSO) approach and the OLS regression analysis. The paper uses time-series data collected from 2005 to 2021 for 256 prefectural-level city districts in China. The authors introduce a new urban spatial house-to-price ratio that adds commuting costs due to spatial endowment compared to the traditional house-to-price ratio. In addition, the paper, compared with the use of ordinary economic modeling methods, adopts the post-LASSO variable selection approach combined with the k-fold cross-test model to identify the most important drivers of housing affordability, thus better solving the problems of multicollinearity and overfitting. The results show that the urban macroeconomics environment and government regulations have varying degrees of influence on housing affordability in cities. Among them, gross domestic product is the most important influence. The paper provides important implications for policymakers, real estate professionals and researchers. For example, policymakers will be able to design policies that target the most influential factors of housing affordability in their region.
In their paper, Torre and Chen examine the spatial effects of relevant factors on housing price variations, especially under the context of market imperfections. Arguing that few studies have applied methods, such as the hedonic price model, in developing countries, the authors employ both non-spatial and spatial regression models to examine the factors associated with housing prices based on the municipal housing appraisal and web-based real estate sales data sets, respectively, for the city of Quito, Ecuador. Torre and Chen estimated an OLS model and several spatial regression models [i.e. a spatial lag model, a spatial error model and a GWR model] considering a set of 17 variables, including structural, neighborhood and location characteristics. The results suggest that, compared to the OLS model, the spatial regression models are more effective at capturing housing market variations at a granular scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory, effects of some housing attributes on housing prices in different areas of the city. Finally, the results shed light on the importance of spatial approaches to identify complex housing markets.
Acknowledgements
This paper forms part of a special section “Spatial analysis and housing markets”, guest edited by Koech Cheruiyot.