期刊
SUSTAINABILITY
卷 14, 期 24, 页码 -出版社
MDPI
DOI: 10.3390/su142416613
关键词
hedonic method; GIS; geospatial analysis; urban green space; housing prices
This study uses data from Seville to analyze the economic impact of urban green spaces on housing prices. The findings suggest that factors such as living area, number of rooms, age, and number of baths are most relevant in determining housing prices. Additionally, the green area per inhabitant is also included as a significant variable. The research indicates that each square meter of green space per inhabitant raises the housing value by 120.19 euro/m(2).
The city of Seville (Spain) is made up of a historical network of pre-existing city overlaps, which increase the economic and heritage value of certain urban areas. To date, green spaces are one of the most important variables in determining the economic value of housing. Thus, this paper uses the hedonic technique and geostatistical analysis with GIS as a methodological approach to infer the economic influence of urban green spaces on housing prices. Along with the traditional variables used to explain dwelling prices, the size of the green space has also been taken into account as an environmental variable affecting prices. The sample consists of 1000 observations collected from Seville. According to the findings, the most relevant variables depend on the hedonic model. Still, in general terms, a dwelling's selling price is related to basic explanatory variables such as living area, number of rooms, age, and number of baths. The green area per inhabitant present in a dwelling's district is also included as part of these basic explanatory variables. In conclusion, the hedonic linear model is the model that best fits housing prices where the values are similar to those obtained by kriging regardless of the district. Based on this research, each square meter of green space per inhabitant in a district raises the housing value by 120.19 euro/m(2).
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