Urban morphology and housing market

• Main Author: Xiao, Yang
• Published: Cardiff University 2012
• Subjects: 307.1; G Geography (General)
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.567530

Urban morphology has been a longstanding field of interest for geographers but without adequate focus on its economic significance. From an economic perspective, urban morphology appears to be a fundamental determinant of house prices since morphology influences accessibility. This PhD thesis investigates the question of how the housing market values urban morphology. Specifically, it investigates people’s revealed preferences for street patterns. The research looks at two distinct types of housing market, one in the UK and the other in China, exploring both static and dynamic relationships between urban morphology and house price. A network analysis method known as space syntax is employed to quantify urban morphology features by computing systemic spatial accessibility indices from a model of a city’s street network. Three research questions are empirically tested. Firstly, does urban configuration influence property value, measured at either individual or aggregate (census output area) level, using the Cardiff housing market as a case study? The second empirical study investigates whether urban configurational features can be used to better delineate housing submarkets. Cardiff is again used as the case study. Thirdly, the research aims to find out how continuous change to the urban street network influences house price volatility at a micro-level. Data from Nanjing, China,is used to investigate this dynamic relationship. The results show that urban morphology does, in fact, have a statistically significant impact on housing price in these two distinctly different housing markets. I find that urban network morphology features can have both positive and negative impacts on housing price. By measuring different types of connectivity in a street network it is possible to identify which parts of the network are likely to have negative accessibility premiums (locations likely to be congested) and which parts are likely to have positive premiums (locations highly connected to destination opportunities). In the China case study, I find that this relationship holds dynamically as well as statically, showing evidence that price change is correlated with some aspects of network change.