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The application of surface generated interpolation models for the prediction of residential property values

William J. McCluskey (School of the Built Environment, University of Ulster, Northern Ireland)
William G. Deddis (School of the Built Environment, University of Ulster, Northern Ireland)
Ian G. Lamont (Causeway Data Communications, University of Ulster, Northern Ireland)
Richard A. Borst ( Cole Layer Trumble, Pennsylvania, USA)

Journal of Property Investment & Finance

ISSN: 1463-578X

Article publication date: 1 April 2000

Abstract

The aim of this paper is to attempt to measure the effect of location on residential house prices and to endeavour to integrate spatial and aspatial data in terms of developing a hybrid predictive model. The research methodology investigates the traditional hedonic approach to modelling location using multiple regression techniques. Alternative approaches are considered which specifically model the spatial distribution of house prices with the objective of developing location adjustment factors. These approaches are based on the development of surface response techniques such as inverse distance weighting and universal kriging. The results generated from the surfaces created are then calibrated within MRA.

Keywords

Citation

McCluskey, W.J., Deddis, W.G., Lamont, I.G. and Borst, R.A. (2000), "The application of surface generated interpolation models for the prediction of residential property values", Journal of Property Investment & Finance, Vol. 18 No. 2, pp. 162-176. https://doi.org/10.1108/14635780010324321

Publisher

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MCB UP Ltd

Copyright © 2000, MCB UP Limited