A Geographically Weighted Regression Method to Spatially Disaggregate Regional Employment Forecasts for South East Queensland

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Title A Geographically Weighted Regression Method to Spatially Disaggregate Regional Employment Forecasts for South East Queensland
Author Li, Terry; Corcoran, Jonathan; Pullar, David; Robson, Alistair; Stimson, Robert
Journal Name Applied Spatial Analysis and Policy
Year Published 2009
Place of publication Netherlands
Publisher Springer
Abstract In this paper we present a new methodology by which regional employment forecasts can be spatially disaggregated to smaller administrative units. We develop a statistical model for disaggregating spatial data based upon related employment determinants (for example, the proximity of an area to a shopping centre), demonstrating there is a degree of spatial dependence and spatial heterogeneity in relationships. Applying an advanced statistical procedure, Geographically Weighted Regression (GWR), to account for these spatial effects this method utilises the locally fitted relationships to estimate employment numbers at the smaller geography whilst being constrained by the regional forecast. Results demonstrate that our GWR method generates superior estimates over a global regression model for spatially disaggregating regional employment forecasts.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/s12061-008-9015-3
Volume 2
Issue Number 2
Page from 147
Page to 175
ISSN 1874-463X
Date Accessioned 2009-09-21
Date Available 2010-07-07T07:39:54Z
Language en_AU
Research Centre Urban Research Program
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Economic Models and Forecasting
URI http://hdl.handle.net/10072/29325
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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