Exploring the many housing elasticities of supply: The case of Australia. (September 2022)

• Record Type: Journal Article
• Authors: Melser, Daniel; ViforJ, Rachel Ong; Wood, Gavin
• Is Part Of: Cities. Volume 128(2022)
• Publication Date: 2022-09
• Subjects: R31 -- C23 -- R12; Housing elasticity of supply -- Urban and regional economics -- Local government areas -- Australia -- Instrumental variables; City planning -- Periodicals; Urban policy -- Periodicals; 711.4
• DOI: 10.1016/j.cities.2022.103817
• Languages: English
• ISSNs: 0264-2751

Abstract

Abstract: The housing elasticity of supply (HES)—how housing supply responds to price rises—has been a major preoccupation of policymakers in the face of worsening housing affordability in many countries. Yet we lack an understanding of just how this quantity varies across regions, and within cities, or the factors which drive it. We address this question by estimating the HES for 341 spatially disaggregated Australian local government areas (LGAs) from 2001 to 2019 for houses and units (attached homes). Our estimates document considerable variation in HES estimates across LGAs. For houses it ranges from 0.17 at the 25th percentile to 0.44 at the 75th percentile while for units it varies between 0.56 and 1.17. Interestingly, we find no correlation between the LGA HES estimates for houses and units. We explore how variation in the local HES relates to potential housing supply drivers such as accessibility to central business districts, topography, temperature range, annual precipitation, and political orientation. The most important driver of the HES is accessibility—LGAs on the city-fringe have the highest HES for houses, while for units it is highest in the inner-city. We find political orientation and annual precipitation have some impact on the HES for units. Highlights: The housing elasticity of supply (HES) is estimated, for houses and units, across disaggregated regions in Australia. The HES for houses is inelastic, averaging around 0.3, while it is much higher, at around 1.0 on average, for units. We find significant dispersion in the HES across local government areas. The spatial variation in the HES is driven by state effects and a region's accessibility to the centre of the city. Factors such as topography, precipitation, temperature, and political orientation have a secondary role in driving the HES.