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• W3113229890 abstract "Hedonic house price models are frequently used to improve our understanding of local housing markets. In recent years, rich registers containing details about home-qualities and neighbourhood characteristics have successfully been coupled with spatial qualities such as job-accessibility or distances to transport. Additional data sources provided by Open data communities, NGOs, data created by governmental agencies on regional national and international level has the potential of being very useful for analysing housing prices. However, the recent methodological advances in GIS and spatial analysis have not been extensively applied. We expand the hedonic price modelling toolbox with geo-coded free data on environmental amenities. We specifically include local measures describing the view-shed, and more varied specifications of access or dominance of green and blue amenities, in addition to urban public-type service and sport facilities. The GIS-derived data is used to study how the variables should be specified and to study their ability to improve even well specified hedonic price models. To our knowledge, this paper is the first to combine all the listed environmental properties in a hedonic model, and at the same time controlling for a large number of other important local neighbourhood characteristics." @default.
• W3113229890 created "2020-12-21" @default.
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• W3113229890 date "2021-01-21" @default.
• W3113229890 modified "2023-10-11" @default.
• W3113229890 title "House price valuation of environmental amenities: An application of GIS‐derived data" @default.
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• W3113229890 doi "https://doi.org/10.1111/rsp3.12382" @default.
• W3113229890 hasPublicationYear "2021" @default.
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