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Implicit Prices in Urban Real Estate Valuation

dc.creatorNúñez Tabales, J; University of Córdoba, Faculty of Economics Puerta Nueva
dc.date2016-05-10
dc.date.accessioned2019-05-03T12:20:09Z
dc.date.available2019-05-03T12:20:09Z
dc.identifierhttp://revistadelaconstruccion.uc.cl/index.php/rdlc/article/view/529
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/84105
dc.descriptionEconometric hedonic models encounterseveral theoretical and practicaldifficulties when applied to the realestate market, such as downwardbiases in the estimation of hedonicprices, subjective decisions in themeasurement process of categoricalattributes, frontier problems related toan imperfect information frameworkand uniequational specification. Manyof these are linked to the parametricapproach.Artificial Neural Networks (ANN)provide an attractive alternative: betterdwelling prices estimates, avoidanceof bias at different market segments,direct use of categorical data and fulluse of the information available. Theprice to be paid is the difficulties inthe economic interpretation of networkparameters. Nowadays, if the finalobjective to produce better estimates ofthe transaction prices, this methodologyshow lower errors, provided of a broadrepresentative database of sales arerecorded. A case study is presentedfor a medium size city in the South ofSpain.Keywords: Urban Economics; Hedonic Models; Neural Networks.en-US
dc.formatapplication/pdf
dc.languageeng
dc.publisherPONTIFICIA UNIVERSIDAD CATOLICA DE CHILEen-US
dc.relationhttp://revistadelaconstruccion.uc.cl/index.php/rdlc/article/view/529/125
dc.sourceRevista de la Construcción. Journal of Construction; 2002-2013 Archivo Revista de la Construccionen-US
dc.source0718-915X
dc.source0717-7925
dc.titleImplicit Prices in Urban Real Estate Valuationen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Articleen-US


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