Editorial note: Housing and in particular affordable housing is such an important issue to the disability sector that we are publishing this article. People with disabilities often have lower incomes caused by no, or under employment, and hence need government subsidised housing or affordable housing rather than the very expensive city accommodation.
A suitable construction funding model is the critical missing ingredient needed to deliver more affordable housing in Australia. Aside from short-lived programs under the Rudd government, we have seen decades of inconsistent and fragmented policies loosely directed at increasing affordable housing. These have failed to generate anything like enough new supply to meet outstanding needs.
Our latest research looked at recently built, larger-scale affordable housing projects in contrasting markets across Australia. We examined each scheme’s cost, funding sources and outcomes. We then developed a housing needs-driven model for understanding the financial and funding requirements to develop affordable housing in the diverse local conditions across the country.
Up to now, the key stumbling block has been the “funding gap” between revenue from rents paid by low-income tenants and the cost of developing and maintaining good-quality housing. The Commonwealth Treasury acknowledged this problem last year. And the problem is greatest in the urban areas where affordable housing is most needed.
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What does the new model tell us?
The Affordable Housing Assessment Tool (AHAT) enables the user to calculate cost-effective ways to fund affordable housing to meet specified needs in different markets. It’s a flexible interactive spreadsheet model with an innovative feature: it enables users to embed housing needs as the driver of project and policy, rather than project financial feasibility driving who can be housed.
Affordable housing developments have recently been relatively sparse. However, our research highlighted the varied and bespoke funding arrangements being used.
Despite this variety, too often project outcomes are driven purely by funding opportunities and constraints, rather than by defined housing needs. One notable constraint is the fragmented nature of affordable housing subsidy frameworks both within and across jurisdictions.
Our case study projects generated a diversity of housing outcomes. This can be seen as an unintended positive of the bespoke nature of affordable housing provision as a result of the need to “stitch together” gap funding from multiple sources on a project-by-project basis.
Equally though, the lack of policy coherence and fit-for-purpose funding added cost and complexity to the development process. By implication, this leads to a less-than-optimal outcome for public investment. Despite providers’ best efforts, current approaches are not the most efficient way to deliver much-needed affordable housing.
What are the lessons from this research?
We applied the model to typical housing development scenarios in inner and outer metropolitan areas and regions. By doing so, we identified six key lessons for funding and financing affordable housing delivery.
1) Government help with access to land is central to affordable housing development and enhances long-term project viability.
Especially in high-pressure urban markets, not-for-profit housing developers cannot compete with the private sector for development sites. High land costs, particularly in inner cities where affordable housing demand is most extreme, can render financial viability near impossible. Having access to sites and lower-cost land were two of the most important components of feasible projects.
2) Government equity investment offers considerable potential for delivering feasible projects and net benefit to government.
How governments treat the valuation of public land with potential for affordable housing development must be reviewed. Conventionally, even where affordable housing is the intended use, governments typically insist on a land sale price based on “highest and best use”.
It would be preferable in such cases to treat the below-market value assigned to public land as a transparent subsidy input. This would mean the sale price reflects the housing needs that the development seeks to meet. That is, the land value should be priced as an affordable housing development for a specific needs cohort.
By retaining an equity stake, government could account for its input as an investment that will increase in value over time as land values appreciate.
3) Reducing up-front debt load and lowering finance costs are critical to long-term project viability.
Debt funding imposes a large cost burden over a project’s lifetime. This is ultimately paid down through tenant rents. Reducing both the cost and scale of private financing can have a significant impact on project viability.
The analysis reinforces the rationale for the Australian government’s “bond aggregator” facility for reducing financing costs for affordable housing projects. But this must come in tandem with other measures to reduce up-front debt.
4) Delivery across the range of housing needs helps to meet overall social and tenure mix objectives. This also can help improve project viability through cross-subsidy.
Mixing tenure and tenant profiles can enable affordable housing providers to produce more diverse housing that meets the full range of needs.
Cross-subsidy opportunities arising from mixed-tenure and mixed-use developments can also enhance project feasibility. By improving a provider’s financial position, this helps advance their long-term goal of adding to the stock of affordable housing. And, by providing welcome flexibility, this enables organisations to better manage development risk across different markets and cycles.
5) The financial benefit of planning bonuses is limited
Inclusionary zoning mechanisms impose affordable housing obligations on developers through the planning system. This approach potentially offers a means of securing affordable housing development sites in larger urban renewal or master-planned areas.
However, our research demonstrated that planning bonuses allowing increased dwelling numbers in return for more affordable housing have little beneficial impact on project viability. This is because the additional dwellings allowed generate additional land and/or construction costs but no matching capacity to service a larger debt.
However, planning bonuses can be useful as part of a cross-subsidy approach. In this case, they may support project viability, without necessarily resulting in any additional affordable dwellings.
6) Increasing the scale of not-for-profit provision offers financial benefits that help ensure the long-term delivery of affordable housing.
Our analysis supports the case for targeting public subsidy to not-for-profit developers (government or non-government) to maximise long-term social benefit. Investing in permanently affordable housing ensures the social dividend of affordable housing can be continued into the future.
Comparable subsidies are not preserved when allocated to private owners. They will seek to trade out at some stage, capitalising the subsidy into privatised gain.
The results of our case study analyses and modelling highlight the need to develop comprehensive funding and subsidy arrangements that account for different costs in different locations. These arrangements also must be integrated nationally to support affordable housing delivery at scale.
This study reiterates the common finding of research over the last decade: both Commonwealth and state/territory governments need to develop a coherent and long-term policy framework to provide housing across the full spectrum of need.
Laurence Troy, Research Fellow, City Futures Research Centre, UNSW; Bill Randolph, Director, City Futures – Faculty Leadership, City Futures Research Centre, Urban Analytics and City Data, Infrastructure in the Built Environment, UNSW; Ryan van den Nouwelant, Senior Research Officer – City Futures Research Centre, UNSW, and Vivienne Milligan, Visiting Senior Fellow – City Futures Research Centre, Housing Policy and Practice, UNSW