Crespo, Ricardo and Fotheringham, Stewart and Charlton, Martin
(2007)
Application of Geographically Weighted Regression to
a 19-year set of house price data in London to
calibrate local hedonic price models.
Proceedings of the 9th International Conference on GeoComputation.
Abstract
In spite of literature on hedonic house price models is quite vast, much more efforts
must be made to integrate and to model spatiotemporal data (see Cressie, 1993).
Nevertheless, it is worth mentioning that excellent works have been done in recent
years to deal with this phenomenon. For example, of paricular interest has been the
research on panel data models (Holly et al., 2006) and spatiotemporal autoregressive
(STAR) models (Pace et al., 1998).
On the other hand, the development of geographically weighted regression
(Brunsdon et al., 1998) has brought new insights into the understanding of spatial
dynamics in econometric models. In this respect, we do believe that the incorporation
of temporal data into the model and the subsequent development of a spatiotemporal
version of GWR will naturally contribute to a better understanding of stochastic
processes that vary and interact in space and time.
This is presicely the aim of this study, that is, to develop a spatiotemporal version
of the GWR technique, which would enable the forecasting of and eventually the
interpolation of local parameters throughout time.
| Item Type: |
Article
|
| Keywords: |
Geographically Weighted Regression; 19-year set; house price data; London; local hedonic price models; |
| Academic Unit: |
Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG |
| Item ID: |
5816 |
| Depositing User: |
Martin Charlton
|
| Date Deposited: |
11 Feb 2015 12:14 |
| Journal or Publication Title: |
Proceedings of the 9th International Conference on GeoComputation |
| Publisher: |
National University of Ireland Maynooth |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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