Examining the spatial and non-spatial linkages between suburban housing markets

Morteza Moallemi, Daniel Melser, Ashton de Silva and Xiaoyan Chen

International Journal of Housing Markets and Analysis, 2021, vol. 15, issue 5, 1170-1194

Abstract: Purpose - The purpose of this paper is on developing and implementing a model which provides a fuller and more comprehensive reflection of the interaction of house prices at the suburb level. Design/methodology/approach - The authors examine how changes in housing prices evolve across space within the suburban context. In doing so, the authors developed a model which allows for suburbs to be connected both because of their geographic proximity but also by non-spatial factors, such as similarities in socioeconomic or demographic characteristics. This approach is applied to modelling home price dynamics in Melbourne, Australia, from 2007 to 2018. Findings - The authors found that including both spatial and non-spatial linkages between suburbs provides a better representation of the data. It also provides new insights into the way spatial shocks are transmitted around the city and how suburban housing markets are clustered. Originality/value - The authors have generalized the widely used SAR model and advocated building a spatial weights matrix that allows for both geographic and socioeconomic linkages between suburbs within the HOSAR framework. As the authors outlined, such a model can be easily estimated using maximum likelihood. The benefits of such a model are that it yields an improved fit to the data and more accurate spatial spill-over estimates.

Keywords: Housing prices; Higher-order spatial autoregression; Socioeconomic characteristics; Melbourne; Intra-city housing market; Suburban housing market; R31; C21 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijhmap:ijhma-07-2021-0082

DOI: 10.1108/IJHMA-07-2021-0082

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