Spatially Disaggregated Modelling of Voting Outcomes and Socio-Economic Characteristics at the 2001 Australian Federal Election

Datos Bibliográficos

ID5877426
AutoresRobert Stimson, Robert J Stimson (The University of Queensland, autor de correspondencia), Rod Mccrea (0000-0003-0066-6577, The University of Queensland), Tung‐kai Shyy, Tung-Kai Shyy (The University of Queensland)
Año2006
Volumen44
Número3
Páginas242-254
Fecha de publicación2006-09-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaGeographical Research (JOURNAL)
Identificadores de la revistaISSN: 1745-5863 • E-ISSN: 1745-5871
EditorialWiley (PUBLISHER • GB)
DOI10.1111/j.1745-5871.2006.00402.x
OpenAlexW2031079984
IdiomaEN
Referencias citadas7

This study uses GIS and spatial modelling to relate voting outcomes at the 2001 federal election for polling booths across Australia with the socio-economic characteristics of polling booth catchment areas. The data and analysis used are more detailed and comprehensive than previous studies. It is conducted at a fine level of spatial disaggregation across the whole nation to examine voting outcomes for both major and minor political parties. Because the aim of the paper is to distinguish voting outcomes between political parties rather than to predict voting outcomes for particular political parties, a discriminant analysis is used rather than regression analysis. The statistical discriminant analysis identifies two main socio-economic dimensions that are able to predict polling booth outcomes with a relatively high degree of accuracy. That analysis shows how, at the 2001 federal election, the middle ground, in terms of socio-economic characteristics, was being claimed by the Liberal Party, Country Liberal Party, The Greens, and, to a lesser extent, by the Australian Labor Party. However, the Australian Democrats, National Party and One Nation had more distinctive constituencies, with the National Party and One Nation Party competing for areas with similar socio-economic characteristics. Using GIS mapping tools, examples of actual and predicted polling booth voting outcomes are given, along with selected socio-economic characteristics of booth catchments

Economics · Geography · Linear discriminant analysis · Political science · Politics · Polling · Public economics · Ranked voting system · Split-ticket voting · Statistics · Voting · Computer Science · Law · Public Administration · Rural development and sustainability · Spatial and Panel Data Analysis · Urban, Neighborhood, and Segregation Studies