The Price Impact of House Refurbishment Estimated by Geographically Weighted Regression and Hedonic Pricing Model
Main Article Content
Abstract
Geographically Weighted Regression (GWR) is a technique that extends the traditional regression framework by allowing spatial parameters to be explicitly estimated. This paper provides a brief description of the Geographically Weighted Regression used here to value the effect of residential housing refurbishment in the City of Kaohsiung (Taiwan). The GWR results are then compared to a standard hedonic pricing estimation model applied to the same data set. What is intended here is to illustrate the use of a better tool for the identification of the spatial price impact of housing improvement investments in the metropolitan area. More generally, the paper confirms that spatial-adaptable models are required to measure the impact of investments in mixed and fuzzy goods.
Downloads
Article Details
COPYRIGHT. All rights reserved. No part of this journal may be reproduced, copied or transmitted, in any form or by any means, electronic, mechanical, photocopying, and recording or otherwise without proper written permission from the publisher. Any opinion expressed in the articles are those of the authors and do not reflect that of the Universiti Malaya, 50603 Kuala Lumpur, Malaysia