Existing housing assistance forecasts fail to assess early intervention points, risk pathways and household resilience. This project uses HILDA and ABS data to develop national predictive models of the impact of life events on housing outcomes, and short- and long-term housing assistance need in the context of risk pathways.

Existing forecasts of housing assistance (Rowley et al., 2017) are based on expressed demand coupled with population forecasting that do not take account of complex interactions of upstream, contributing factors that result in the need for households to seek housing assistance. As such, they provide limited evidence about how housing policy development can be geared toward a proactive, early interventionist role. Understanding the impact of ‘critical life events’ (CLEs) and housing shocks that lead to the need for housing assistance is critical to: (i) support innovative policy interventions that seek to intervene early and reduce long-term cost to governments, individuals and society; (ii) enable most effective targeting of housing assistance to households in need and; (iii) assess the ways in which household resources interact with housing assistance in short- and long-term models of housing assistance provision. This project interrogates national longitudinal data to examine the impact of CLEs on housing outcomes to develop a set of predictive models of ‘risk pathways’ to address this critical knowledge gap.