The geography of homelessness in Australia
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1 The geography of homelessness in Australia Gavin Wood, Deb Batterham, Melek Cigdem and Shelley Mallett Centre for Urban Research RMIT University & Launch Housing
2 Some of our research questions Where is homelessness high and where is it low? Where is homelessness rising or falling? Is homelessness becoming more or less spatially concentrated? Are homelessness services well located to intervene in areas with high and rising rates of homelessness? What explains these geographical differences? The composition of the homeless population? Housing and labour markets?
3 Two key measures of homelessness The rate per 10,000 persons The national share of homelessness
4 The top and bottom 20 SA3 regions with the highest/lowest rate of homelessness per 10,000 in 2011
5 The top and bottom 20 SA3s with the highest/lowest share of national homelessness in 2011
6 The percent change in the rate of homelessness per 10,000 persons from
7 How spatially concentrated is homelessness?
8 Are homelessness services will placed? There is higher service capacity in areas with a higher rate of homelessness We found evidence of a degree of mismatch Mismatch measure suggested a third of accommodation capacity needs to shift across SA3s boundaries
9 Where is the biggest mismatch?
10
11 What role does the composition of the homeless population play? Composition = 6 operational groups Shift-share analysis suggested not much.
12 What else might be driving these differences? Two levels of findings : Descriptives examining bivariate (one to one) relationships between each indicator and rates of homelessness. Panel modelling
13 Some descriptive results : the supply of affordable housing Homeless rates higher in regions with a larger supply of affordable housing relative to demand from low-income households (defined using the 30/40 rule) Acute shortage of affordable one-bedroom private rental dwellings, larger dwelling sizes (two or more bedrooms) seemed to be better supplied Homeless rates fell in regions with a better supply of affordable rental housing and rose in areas with more of a shortage.
14 Modelling some key findings Demographic characteristics - males, young, sole parents, indigenous Income inequality??supply of affordable housing and labour markets??
15 Key features of 3 regions Gippsland and the Central Highlands/Grampians: Have lower rates of homelessness and experienced a decrease over the decade. Have higher service capacity than Victorian and national average Southern metro: Has higher rates of homelessness and has experienced an increase over the decade. Has more accommodation places, but not relative to the size of its homeless population. These places are concentrated in Greater Dandenong where homelessness is highest in that region. All three regions have a better supply of affordable private rental housing relative to demand
16 Questions for panel Given what we know about homelessness and other factors in your areas if you were in charge of a big bucket of money, a bucket that will not meet all the needs but will meet say 2/3rds of need, how would you allocate it in your region and why? What do you see as the most common causes of homelessness in your area? Is there a way you think these could be addressed in order to prevent or reduce homelessness in your region?
17 ahuri.edu.au
18 Key variables Housing Market (median rents, dwelling and tenure composition, rent to income ratios, supply of affordable housing) Income and Income inequality (household income; rent to income ratios, Gini coefficients) Labour Market (unemployment, part time employment, unskilled work, education) Demographic characteristics (age, gender, household type, indigenous, marital status,..) Climate (summer and winter temperatures, climate variability)
19 How do we make sense of these findings? REGION A REGION B Population Median Rent per week $300 $600 Unemployment Rate 12% 3% Median household income per week $900 $1800 Public Housing as % of all households 7% 2% At risk group 8 2 Homeless 2 1 Homeless rate per Homeless as per cent of at risk group 25% 50%
Australian demographic trends and implications for housing assistance programs PEER REVIEWED EXECUTIVE SUMMARY
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