Homelessness continues to be a feature of wealthy nations, and most recently, has dominated Victorian front page news, as the figures of people sleeping rough on the streets of Melbourne rise.
In order to develop effective policies to prevent or alleviate homelessness it’s important to understand what causes people to enter homelessness and then prevents them from finding adequate housing.
A lack of affordable housing can lift homelessness numbers, and supply side constraints can contribute to shortages of affordable housing. These supply constraints can arise for a number reasons. For example, structural features such as areas with steep inclines or flood plains are costlier to develop, while regulation of land and buildings, as well as bottlenecks within the building construction industry, such as skill shortages, can all contribute. These supply constraints may prevent the expansion of low-cost rental to accommodate those displaced, and homelessness results.
Local labour market conditions is also likely to affect individual risks of homelessness, as those in areas with weak labour markets are more likely to experience negative income shocks associated with unemployment.
Recent empirical studies examining the effect of housing and labour markets have primarily been dominated by analyses conducted at the city-level. Most area-level studies use cross-sectional data to explain the inter-city variations in homelessness.
In a recent study with Associate Professor Guy Johnson, RMIT University, and Dr Rosanna Scutella and Dr Yi-Ping Tseng at Melbourne Institute of Applied Economic and Social Research, we examine the overall impact of housing and labour markets on individual risks of homelessness, exploring the relationship between area-level structural conditions, individual characteristics and transitions into and out of homelessness. This is achieved by combining micro-level longitudinal data obtained from 1682 Australian welfare recipients (the Journeys Home Survey), with area-level observations of housing and labour market conditions to explore the relationship between structural conditions, individual characteristics and transitions into and out of homelessness.
In addition to this, we also examine whether there is a heterogeneous impact across individuals with different characteristics. That is, do housing and labour market conditions affect those with particular risk factors such as mental illness, physical illness, substance misuse, and/or histories of incarceration more than others?
To undertake our analysis, three econometric models were developed. The first model (the static model) examines the probability of being homeless at any wave in the Journeys Home study – an interviewer-administered survey that followed a large sample of Australian income support recipients exposed to homelessness or housing insecurity over time. The second examines the probability of entry into homelessness; and the third the probability of exiting homelessness. As the probability of being homeless reflects entry into and exit from homelessness we focus on the second and third models.
Among disadvantaged Australians the risk of homelessness is higher among people with low levels of education, the unemployed, and those with recent experience of violence or incarceration.
Vulnerable people with biographies marked by acute disadvantage such as fewer years of schooling, no previous record of employment and past episodes of homelessness are more likely to slip into homelessness.
The results also suggested that the risk of becoming homeless is greater in regions with higher rents and slack labour markets; residence in public housing has a strong protective effect.
For certain groups it is being the ‘wrong person in the wrong place’ that matters most when considering risks of entering homelessness. Indigenous people, for example, are no more likely to become homeless than other vulnerable groups holding housing and labour market conditions constant. But if local housing markets tighten, or local labour markets slump, the Indigenous become more prone to homelessness.
The processes shaping pathways out of homelessness appear to be very different from those shaping entries into homelessness. We found that for those with risky behaviours, programs that directly address these behaviours are the optimal approach to reduce entries into homelessness.
Our results suggest that personal characteristics and housing and labour market conditions are a generally unimportant influence on pathways out of homelessness. Age however, is one exception to this proposition.
Older homeless people are found to be much less likely to escape their predicament. These results suggest that when an older individual is homeless they become disconnected from housing and labour markets. Age could be the key influence because young people are more adaptable as well as more mobile, and hence have access to a wider range of housing and labour market opportunities.
Our results emphasise the importance of modelling both entries into and exits from homelessness as behavioural traits and structural housing and labour market conditions can have different impacts on transitions into and out of homelessness.
Understanding how housing and labour market conditions interact with individual characteristics to influence the risk of becoming homeless and the probability of exiting homelessness is critical information if policy-makers are to design and locate appropriate program responses.