House Price Prediction: Hedonic Price Model vs. Artificial Neural Network

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No 97781, 2004 Conference, June 25-26, 2004, Blenheim, New Zealand from New Zealand Agricultural and Resource Economics Society

Abstract: 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.

Keywords: Environmental Economics and Policy; Land Economics/Use; Research Methods/ Statistical Methods (search for similar items in EconPapers)
Pages: 15
Date: 2004-06
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Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:nzar04:97781

DOI: 10.22004/ag.econ.97781

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