A systems approach to housing market analysis : the role of search and migration in market dynamics in Greater Manchester

• Main Author: Doan, L. V. Lam
• Other Authors: Watkins, Craig ; Rae, Alasdair
• Published: University of Sheffield 2017
• Subjects: 363.5
• Online Access: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.723223

Housing markets are complex and dynamic entities. They are fragmented across space and their structure and functionality alters over time. This complexity makes monitoring and steering markets difficult and is one of the reasons that planning for housing is analytically and technically challenging. To analyse housing effectively, it is widely held that we should conceptualise the market as a part of a system of linked but spatially coherent Housing Markets Areas, comprising internally of inter-linked submarkets that are over time subject to changes in configuration and function. In response, this thesis adopts a systems approach to frame the analysis of housing market dynamics (O’Sullivan et al, 2004). Within this framework, the study aims to understand the spatial and temporal dynamics of the Greater Manchester housing system in recent years. The analysis seeks to demonstrate the usefulness of a market systems approach that employs visual data analytical methods to provide insights into market processes. Specifically the thesis analyses housing search, migration and house price and offers a case study that explores the interactions between HMAs, and submarket connections within an HMA. The major contribution is to highlight the importance of considering a housing market as a system of linked HMAs and submarkets, to illustrate the useful insights that might be generated using visual data methods and to provide a novel analysis that combines role of housing search, migration and house price data in gaining a better understanding of how a local housing market works. In doing so, the study is at the forefront of the emerging literature that uses new micro-datasets to analyse search information.