Implicit Prices in Urban Real Estate Valuation
Econometric hedonic models encounter several theoretical and practical difficulties when applied to the real estate market, such as downward biases in the estimation of hedonic prices, subjective decisions in the measurement process of categorical attributes, frontier problems related to an imperfec...
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Escuela de Construcción Civil, Pontificia Universidad Católica de Chile
2013
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oai:scielo:S0718-915X20130002000092014-08-18Implicit Prices in Urban Real Estate ValuationNúñez Tabales,JRey Carmona,FCaridad y Ocerin,J. Mª Urban Economics Hedonic Models Neural Networks Econometric hedonic models encounter several theoretical and practical difficulties when applied to the real estate market, such as downward biases in the estimation of hedonic prices, subjective decisions in the measurement process of categorical attributes, frontier problems related to an imperfect information framework and uniequational specification. Many of these are linked to the parametric approach. Artificial Neural Networks (ANN) provide an attractive alternative: better dwelling prices estimates, avoidance of bias at different market segments, direct use of categorical data and full use of the information available. The price to be paid is the difficulties in the economic interpretation of network parameters. Nowadays, if the final objective to produce better estimates of the transaction prices, this methodology show lower errors, provided of a broad representative database of sales are recorded. A case study is presented for a medium size city in the South of Spain.info:eu-repo/semantics/openAccessEscuela de Construcción Civil, Pontificia Universidad Católica de ChileRevista de la construcción v.12 n.2 20132013-11-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2013000200009en10.4067/S0718-915X2013000200009 |
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Scielo Chile |
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Scielo Chile |
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English |
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Urban Economics Hedonic Models Neural Networks |
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Urban Economics Hedonic Models Neural Networks Núñez Tabales,J Rey Carmona,F Caridad y Ocerin,J. Mª Implicit Prices in Urban Real Estate Valuation |
description |
Econometric hedonic models encounter several theoretical and practical difficulties when applied to the real estate market, such as downward biases in the estimation of hedonic prices, subjective decisions in the measurement process of categorical attributes, frontier problems related to an imperfect information framework and uniequational specification. Many of these are linked to the parametric approach. Artificial Neural Networks (ANN) provide an attractive alternative: better dwelling prices estimates, avoidance of bias at different market segments, direct use of categorical data and full use of the information available. The price to be paid is the difficulties in the economic interpretation of network parameters. Nowadays, if the final objective to produce better estimates of the transaction prices, this methodology show lower errors, provided of a broad representative database of sales are recorded. A case study is presented for a medium size city in the South of Spain. |
author |
Núñez Tabales,J Rey Carmona,F Caridad y Ocerin,J. Mª |
author_facet |
Núñez Tabales,J Rey Carmona,F Caridad y Ocerin,J. Mª |
author_sort |
Núñez Tabales,J |
title |
Implicit Prices in Urban Real Estate Valuation |
title_short |
Implicit Prices in Urban Real Estate Valuation |
title_full |
Implicit Prices in Urban Real Estate Valuation |
title_fullStr |
Implicit Prices in Urban Real Estate Valuation |
title_full_unstemmed |
Implicit Prices in Urban Real Estate Valuation |
title_sort |
implicit prices in urban real estate valuation |
publisher |
Escuela de Construcción Civil, Pontificia Universidad Católica de Chile |
publishDate |
2013 |
url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2013000200009 |
work_keys_str_mv |
AT nuneztabalesj implicitpricesinurbanrealestatevaluation AT reycarmonaf implicitpricesinurbanrealestatevaluation AT caridadyocerinjma implicitpricesinurbanrealestatevaluation |
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