Impacts of urban environmental elements on residential housing prices in Guangzhou (China)

The amenity value provided by urban green spaces, water bodies and good environmental quality is difficult to assess and incorporate into urban planning and development. Developers and governments in China hitherto have seldom objectively factored these attributes into property pricing and associated decisions. The hedonic pricing method offers an appropriate approach to gauge such external benefits which contribute to real-estate transaction prices. This study explored the impacts of key environmental elements with a bearing on residential housing value in Guangzhou, including window orientation, green-space view, floor height, proximity to wooded areas and water bodies, and exposure to traffic noise. Four large private housing estates composed of multi-storied blocks with similar design and price bracket, catering to the mass property market, were sampled. Transaction price data and structural attributes of 652 dwelling units were acquired directly from developers. Data on environmental attributes were collected in the field. Two functional hedonic pricing method models, linear and semi-log, were constructed. The semi-log model offered comparatively stronger explanatory power and more reliable estimation. High floor on the multi-storey tenement blocks contributed implicitly 9.2% to the selling price. View of green spaces and proximity to water bodies raised housing price, contributing notably at 7.1% and 13.2%, respectively. Windows with a southern orientation with or without complementary eastern or northern views added 1% to the price. Proximity to nearby wooded area without public access was not significant, expressing the pragmatic mindset in the hedonic behavior. Exposure to traffic noise did not influence willingness-to-pay, implying tolerance of the chronic environmental nuisance in the compact city. The study demonstrates that hedonic pricing method could be applied in the Chinese context with an increasingly expanding and privatized property market. It could inform the decisions of policy makers and property developers concerning land selling and buying, land conversion, property development, urban nature conservation, and design of ecological green-space networks.