Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/120312
Authors: 
Fernández-Durán, Laura
Llorca, Alicia
Ruiz, Nancy
Valero, Soledad
Botti, Vicente
Year of Publication: 
2011
Series/Report no.: 
51st Congress of the European Regional Science Association: "New Challenges for European Regions and Urban Areas in a Globalised World", 30 August - 3 September 2011, Barcelona, Spain
Abstract: 
The location of a residential property in a city directly affects its market price. Each location represents different values in variables such as accessibility, neighbourhood, traffic, socio-economic level and proximity to green areas, among others. In addition, that location has an influence on the choice and on the offer price of each residential property. The development of artificial intelligence, allows us to use alternative tools to the traditional methods of econometric modelling. This has led us to conduct a study of the residential property market in the city of Valencia (Spain). In this study, we will attempt to explain the aspects that determine the demand for housing and the behaviour of prices in the urban space. We used an artificial neutral network as a price forecasting tool, since this system shows a considerable improvement in the accuracy of ratings over traditional models. With the help of this system, we attempted to quantify the impact on residential property prices of issues such as accessibility, level of service standards of public utilities, quality of urban planning, environmental surroundings and other locational aspects.
Document Type: 
Conference Paper

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