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The modelling of housing submarkets

The modelling of housing submarkets This paper is concerned as to whether it is more appropriate to use aggregate or disaggregate models in forecasting house prices using hedonic modelling. It is accepted that the implicit pricing of some of the attributes is not stable between locations, property types and ages but it is argued that this can be effectively modelled with an aggregate method. The models are developed using a dataset of nearly 18,000 transactions in the UK Midlands region in 1994. The comparative performance of these models is then considered using two approaches. Chow tests of the error differences between actual price and the price predicted by the models suggest that the submarket models lead to statistically significant, though small, improvements. A second approach, using comparison of the root mean square errors, is conducted on the models’ forecasts for a 10 per cent sample of nearly 2,000 transactions excluded from the modelling process. This shows little practical difference in the forecasting ability between the two approaches. Great care needs to be taken over sample size if a disaggregate model is used. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Property Investment & Finance Emerald Publishing

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Publisher
Emerald Publishing
Copyright
Copyright © 2000 MCB UP Ltd. All rights reserved.
ISSN
1463-578X
DOI
10.1108/14635780010345436
Publisher site
See Article on Publisher Site

Abstract

This paper is concerned as to whether it is more appropriate to use aggregate or disaggregate models in forecasting house prices using hedonic modelling. It is accepted that the implicit pricing of some of the attributes is not stable between locations, property types and ages but it is argued that this can be effectively modelled with an aggregate method. The models are developed using a dataset of nearly 18,000 transactions in the UK Midlands region in 1994. The comparative performance of these models is then considered using two approaches. Chow tests of the error differences between actual price and the price predicted by the models suggest that the submarket models lead to statistically significant, though small, improvements. A second approach, using comparison of the root mean square errors, is conducted on the models’ forecasts for a 10 per cent sample of nearly 2,000 transactions excluded from the modelling process. This shows little practical difference in the forecasting ability between the two approaches. Great care needs to be taken over sample size if a disaggregate model is used.

Journal

Journal of Property Investment & FinanceEmerald Publishing

Published: Aug 1, 2000

Keywords: Housing markets; Forecasting; Modelling

References