Affordable housing projects are being shaped by constrained funding rather than actual needs, according to a new report by UNSW researchers.

Researchers from the University of New South Wales (UNSW) City Futures Research Centre developed the ‘Affordable Housing Assessment Tool’ (AHAT) to determine how affordable housing project costs, revenues and subsidies impacted affordability for a range of lower income households in need of affordable housing.

Funding opportunities for affordable housing include having access to government land, public and private capital and debt finance, tenant rents, and sales of properties to the private market. The way these sources of funding are combined can add complexity, cost and financial risk to delivering financial housing, say the researchers.

This is leading to instances where for example, due to lack of funding, community housing providers are having to reduce the proportion of their developments dedicated to social and affordable housing to reduce project debt levels that can be serviced by rents from low-income tenants.

“What we have developed for the first time is a tool that enables us to start with housing needs, then figure out which types of subsidies and policies will best be able to fund projects to meet those needs,” says Dr Laurence Troy, one of the researchers.

“By using this tool we also found subsidizing the private sector to produce affordable housing that is available for a defined period of time is less cost-effective over the longer term than directing such subsidies to not-for-profit housing providers.”

 The report makes some policy recommendations to help affordable housing development:

  • Make public land available at below-market cost to support affordable housing development
  • Keep affordable housing in the not-for-profit housing sector to retain for the long term the social benefit created by public investment
  • Encourage mixed tenure developments and development at scale
  • Provide ‘gap funding’ to help reduce the need for private financing
  • Use needs-based modelling for investment decisions and to drive the allocation of subsidies