Modelling the spatial pattern of housing-renovation employment in Melbourne, Australia: an application of geographically weighted regression
journal contributionposted on 21.11.2017 by Kiran KC, Prem Chhetri, Colin Arrowsmith, Jonathan Corcoran
Any type of content formally published in an academic journal, usually following a peer-review process.
This paper discusses research aimed at identifying key factors influencing the distribution of residential housing renovation employment in metropolitan Melbourne. Using Geographically Weighted Regression (GWR), employment focused on residential housing renovation is modelled using six parameters representing urban space: distance to the central business district, median household income, distance to highways, the number of nearby shopping centres, distance to public open space and accessibility to railway stations. Of the six different explanatory variables, the estimated value of the Ordinary Least Square model for distance to CBD and open space were statistically significant. Mapping the values of local coefficient estimates of independent variables revealed their extent of influence and variation in residential housing renovation employment.