Value of playgrounds relative to green spaces: Matching evidence from property prices in Australia

Breunig, Robert; Hasan, Syed; Whiteoak, Kym

doi:10.1016/j.landurbplan.2019.103608

Cited by 10 publications

(2 citation statements)

References 49 publications

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“…As the presence (or absence) of facilities and amenities affects the attractiveness of a given area or location and its related housing prices, many research works address and investigate this issue in different countries worldwide. See, for instance, studies identifying the positive impact of good quality schools (Figlio and Lucas, 2004), presence of sport facilities (Feng and Humphreys, 2018) and better access to railways stations and metro connections (Armstrong and Rodriguez, 2006;Baum-Snow and Kahn, 2000) on residential property values in the US; the housing price premium that a favourable job location combined with a variety of amenities confer to housing prices in the Netherlands (Garresset and Marlet, 2015); and the increase in housing prices resulting from having a playground within spatial proximity in Australian neighbourhoods (Breunig et al, 2019). Moreover, other studies demonstrate how the overall attractiveness and housing prices of residential areas fall in presence of factors such as higher crime rates (Gibbons, 2004), higher levels of pollution (Chen & Chen, 2016) and environmental dis-amenities (e.g.…”

Section: Determinants Of House Prices and The Relationship With Pubsmentioning

confidence: 99%

Public houses and house prices in Great Britain: a panel analysis

Cabras

Sohns

Canduela

et al. 2020

European Planning Studies

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This paper examines the relationship between public houses or 'pubs' and house prices in Great Britain. Using a unique dataset, comprising statistical indicators for 373 local authorities registered between 2005 and 2015, the authors investigate this relationship from a panel data perspective. The analysis identifies a strong positive association between an increase in the number of pubs and house prices, showing different patterns with regard to pubs located in urban, suburban and rural areas. Results offer an original contribution to the literature related to the economic value of pubs as important third places in Great Britain, providing the basis for potential policy choices aimed at supporting community investment.

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Section: Determinants Of House Prices and The Relationship With Pubsmentioning

confidence: 99%

Public houses and house prices in Great Britain: a panel analysis

Cabras

Sohns

Canduela

et al. 2020

European Planning Studies

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“…Table 5 shows the descriptive statistics of GWR. Based on previous HPM studies [39,68], we used the 0.05 significance level as the critical value to determine whether this factor is statistically significant. β is the coefficient of each variable.…”

Section: Gwrmentioning

confidence: 99%

Making the Third Dimension (3D) Explicit in Hedonic Price Modelling: A Case Study of Xi’an, China

Ying

Koeva

Kuffer

et al. 2020

Land

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Recent rapid population growth and increasing urbanisation have led to fast vertical developments in urban areas. Therefore, in the context of the dynamic property market, factors related to the third dimension (3D) need to be considered. Current hedonic price modelling (HPM) studies have little explicit consideration for the third dimension, which may have a significant influence on modelling property values in complex urban environments. Therefore, our research aims to narrow the cognitive gap of the missing third dimension by assessing both 2D and 3D HPM and identifying important 3D factors for spatial analysis and visualisation in the selected study area, Xi’an, China. The statistical methods we used for 2D HPM are ordinary least squares (OLS) and geographically weighted regression (GWR). In 2D HPM, they both have very low R2 (0.111 in OLS and 0.217 in GWR), showing a very limited generalisation potential. However, a significant improvement is observed when adding 3D factors, namely view quality, sky view factor (SVF), sunlight and property orientation. The obtained higher R2 (0.414) shows the importance of the third dimension or—3D factors for HPM. Our findings demonstrate the necessity to include such factors into HPM and to develop 3D models with a higher level of details (LoD) to serve more purposes such as fair property taxation.

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