Making Housing Assistance More Efficient: A Risk Management Approach

Abstract

Housing affordability has declined in a number of countries over the past 20 years. Governments are under increasing pressure to maximise the reach and effectiveness of housing assistance policies to deal with the resulting problems of increasing housing stress. This paper presents a model, based on Monte Carlo simulation, that estimates the expected subsidy costs required for a range of housing assistance policy approaches, assuming that an affordability benchmark is met. The required subsidies reflect and vary with the systematic risk factors characterising different regional housing markets, suggesting that significant subsidy cost savings can be gained by tailoring particular policy mixes to each market. The model is applied to Australia's eight state capital cities.