TY - JOUR
T1 - Classification and valuation of urban green spaces
T2 - a hedonic house price valuation
AU - Panduro, Toke Emil
AU - Veie, Kathrine Lausted
N1 - Available online 9 September 2013
PY - 2013/12
Y1 - 2013/12
N2 - In this paper we propose a categorization of green space into eight different types and quantify their impact on housing prices in the city of Aalborg using the hedonic house price method. The categorization was made manually according to an idealized description of the eight types of green space and a rating system in which each green space was rated according to accessibility, maintenance levels and neighboring negative land-use. The hedonic house price schedule for each of the green spaces was estimated using a generalized additive model, which allows for a data driven adjustment of underlying omitted spatial processes. To our knowledge the use of a spatial generalized additive model is novel to the hedonic valuation literature. We find that types of green space, which are rated highly in terms of accessibility and maintenance level, have high implicit prices whereas types with low ratings are not identified or provide ambiguous results. Green space buffering unattractive land-use such as infrastructure and industry is found to provide negative implicit prices despite controlling for the negative neighboring land-use. Our results clearly indicate that green space is not a uniform environmental amenity but rather a set of distinct goods with very different impacts on the housing price.
AB - In this paper we propose a categorization of green space into eight different types and quantify their impact on housing prices in the city of Aalborg using the hedonic house price method. The categorization was made manually according to an idealized description of the eight types of green space and a rating system in which each green space was rated according to accessibility, maintenance levels and neighboring negative land-use. The hedonic house price schedule for each of the green spaces was estimated using a generalized additive model, which allows for a data driven adjustment of underlying omitted spatial processes. To our knowledge the use of a spatial generalized additive model is novel to the hedonic valuation literature. We find that types of green space, which are rated highly in terms of accessibility and maintenance level, have high implicit prices whereas types with low ratings are not identified or provide ambiguous results. Green space buffering unattractive land-use such as infrastructure and industry is found to provide negative implicit prices despite controlling for the negative neighboring land-use. Our results clearly indicate that green space is not a uniform environmental amenity but rather a set of distinct goods with very different impacts on the housing price.
KW - Faculty of Science
KW - Hedonic valuation
KW - Green space appreciation index
KW - Classification
KW - Environmental amenity and disamenity
U2 - 10.1016/j.landurbplan.2013.08.009
DO - 10.1016/j.landurbplan.2013.08.009
M3 - Journal article
SN - 0169-2046
VL - 120
SP - 119
EP - 128
JO - Landscape and Urban Planning
JF - Landscape and Urban Planning
ER -
