The latest 2016 Australian Census showed that a much lower proportion of people own their house in 2016, and a higher proportion are renting or purchasing. The tax and transfer system is one policy lever controlled by the Commonwealth government that might be able to assist younger families with lower incomes get into the housing market. Modelling these changes to the tax/transfer system requires a socially disaggregated model that operates at household level. Furthermore, as impacts of housing policy are geographically localized, the approach requires a spatially explicit model. These two modelling paradigms have been brought together previously for studying the spatial impact of a policy change, and this research extends this work by joining a tax/transfer microsimulation model with a synthetic census for Australia. Looking at the results of the policy change, low income households and areas in regional Australia benefited the most from the change; and high income households and capital cities lost the most. This was mainly due to the tax increase. Visualising these using the CityViz system provides researchers with the ability to interact with the data, filtering locations, wins and losses, at varied scales (from SA2, regional, state to national level).

Instructions on how to use the above visualisation can be downloaded here