| Registro completo |
| Provedor de dados: |
AgEcon
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| País: |
United States
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| Título: |
House Price Prediction: Hedonic Price Model vs. Artificial Neural Network
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| Autores: |
Limsombunchai, Visit
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| Data: |
2010-12-11
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| Ano: |
2004
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| Palavras-chave: |
Hedonic Model
Artificial Neural Network (ANN)
House Price.
Environmental Economics and Policy
Land Economics/Use
Research Methods/ Statistical Methods
C53
L74
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| Resumo: |
The objective of this paper is to empirically compare the predictive power of the hedonic model with an artificial neural network model on house price prediction. A sample of 200 houses in Christchurch, New Zealand is randomly selected from the Harcourt website. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities around the house and geographical location are considered. Empirical results support the potential of artificial neural network on house price prediction, although previous studies have commented on its black box nature and achieved different conclusions.
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| Tipo: |
Conference Paper or Presentation
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| Idioma: |
Inglês
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| Identificador: |
http://purl.umn.edu/97781
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| Relação: |
New Zealand Agricultural and Resource Economics Society>2004 Conference, June 25-26, 2004, Blenheim, New Zealand
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| Formato: |
15
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