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Small area housing stress estimation in Australia: Calculating confidence intervals for a spatial microsimulation model
Authors:Azizur Rahman
Institution:1. Discipline of Mathematics and Statistics, School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW, Australia;2. National Centre for Social and Economic Modelling (NATSEM), University of Canberra, Australia
Abstract:This study provides small area housing stress estimates by tenure type in Australia with a way of calculating confidence intervals for a spatial microsimulation model. Findings reveal that prevalence of housing stress for private-renter, buyer, public-renter and owner households are 59.6%, 33.2%, 6.9%, and 0.3%, respectively. Almost two-thirds of these households are located in statistical local areas (SLAs) in eight capital cities, and a large number of them are in Sydney and Melbourne. Estimates for private renters and buyers are significantly high in some capitals and southeast coastal regions. About 95.7% of SLAs show accurate estimates with narrow confidence intervals.
Keywords:Confidence Intervals  Housing stress  Microsimulation modelling  Small area estimation  Spatial microsimulation
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