Publication Date

2017

Abstract

Housing affordability is traditionally measured using the percentage of household income spent on housing. An important cost that is usually overlooked in measuring location affordability is the transportation or accessibility costs. In this paper, we present a modeling approach, driven by urban open data, to measure location affordability that incorporates both housing and transportation costs. We apply the developed model to assess housing affordability in Melbourne, Australia as a case study. Results suggest that neighbourhoods that appear to be affordable when only housing cost is considered are not necessarily affordable when transportation costs are taken into account. A negative correlation between housing affordability and transportation affordability is observed. We also identify the presence of a strong spatial clustering pattern in the affordability measure across the study area. A major methodological contribution of the paper is the inclusion of comprehensive private vehicle costs and public transportation expenses in the model that contributes to a more robust estimation and understanding of location affordability. The model also distinguishes between different trip purposes. Results suggest that plans and policies to improve housing affordability should be made in coordination with transportation infrastructure investment plans to ensure effective and equitable outcomes. Nevertheless, the focus of the paper is more on the measurement of affordability; rather than reviewing and recommending housing related policies.

School/Institute

School of Arts

Document Type

Journal Article

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