Presentation on theme: "Housing markets and individual risks of homelessness Rosanna Scutella, Gavin Wood, Guy Johnson and Yi-Ping Tseng."— Presentation transcript:
Housing markets and individual risks of homelessness Rosanna Scutella, Gavin Wood, Guy Johnson and Yi-Ping Tseng
www.melbourneinstitute.com Motivation Census data limited –Few individual risk factors –Can’t examine interaction of area level/individual risk factors –Is a static picture: housing and labour markets might affect entries and exits differently and people move across areas Need individual-level longitudinal data that includes: –Homeless + At-risk/Vulnerable –Has spatial variation Journeys Home
www.melbourneinstitute.com Research questions Are individuals more likely to experience homelessness in areas with certain housing or labour market characteristics? Are individuals more likely to enter homelessness in areas with certain housing or labour market characteristics? Are individuals more likely to exit homelessness in areas with certain housing or labour market characteristics?
www.melbourneinstitute.com The data: Journeys Home 5-wave panel of persons facing housing insecurity Population: –Centrelink clients ‘homeless’, ‘at-risk’ or ‘vulnerable to homelessness’. Sample: –stratified by region and clustered: 36 locations –2,992 cases to field Follow all 1,682 wave 1 respondents
www.melbourneinstitute.com Sample Structure (not to scale) Centrelink income support population (4.7m+) Homelessness flags (42,300) − homeless − at risk of homelessness Study sample (2992) − homeless indicator (~1/3) − at risk of homelessness indicator (~1/3) − vulnerable to homelessness (~1/3) Target population (138,000) − includes ‘vulnerable to homelessness’ group
www.melbourneinstitute.com Profile of Respondents (1) JH Wave 1 Australian population Male 54.749.4 Female 45.350.6 15-17 years9.54.8 18-20 years16.55.1 21-24 years12.67.3 25-34 years21.717.7 35-44 years20.017.3 45-54 years14.016.7 55-64 years4.814.1 65+ years0.916.9 Aboriginal or Torres Strait Islander19.72.5 Australian born87.573.2 Born overseas (English-speaking)5.8 26.8 Born overseas (non-English-speaking)6.7 Married/defacto17.363.7 Have dependent children19.833.9 N1,682
www.melbourneinstitute.com Profile of Respondents (2) JH Wave 1 Australian population Highest education qualification Tertiary qualification27.950.2 Completed Yr 12 or equivalent11.320.6 Completed Year 10 or 11 or equivalent39.521.4 Completed Year 9 or below20.17.7 Labour force status Employed20.162.6 Unemployed29.93.4 Not in labour force50.134.0 N1,682
www.melbourneinstitute.com Profile of Respondents (3) JH Wave 1 Australian population 1 Diagnosed mental health condition Bipolar effective disorder11.02.9 Schizophrenia8.9n.a. Depression53.511.6 2 Post-traumatic stress disorder 3 19.712.2 Anxiety disorder 3 41.326.3 Smoking, alcohol consumption and illicit drug use Smokes daily 67.915.1 Consumes alcohol at ‘risky’4 levels 57.420.1 Used illicit drugs in last 6 months/12 months 39.414.7 Injected illicit drugs in last 6 months/12 months 7.30.4 N1,682
www.melbourneinstitute.com Response Outcomes, W2 to W5 OutcomeWave 2Wave 3Wave 4Wave 5 N%N%N%N% Completed interview152990.9147387.6145486.4142184.5 Out of scope*221.3472.8523.1513.0 Non-contact684.0704.2855.1784.6 Other non-response**633.7925.5915.41327.8 TOTAL SAMPLE (W1 resp’ts) 1682100168210016821001682100 * Out of scope includes persons who: have died; are overseas; are in prison; or are in some other institution. ** This category includes outcomes classified as: refusal, termination, incapable, and contact made but no interview resulted.
www.melbourneinstitute.com Defining homelessness Cultural definition –minimum community standard that people expect in contemporary Australian society Includes those: –sleeping rough or squatting; –staying temporarily with others; –in emergency or crisis accommodation; or –in boarding houses Main difference with ABS definition: doesn’t include overcrowding
www.melbourneinstitute.com Prevalence of homelessness Wave 1Wave 2Wave 3Wave 4Wave 5 Males33.426.927.427.024.1 Females18.717.014.911.912.9 15 to 24 years18.815.614.112.510.0 25 to 44 years28.123.522.722.321.3 45 years plus43.434.935.930.930.4 Indigenous18.104.22.168.225.3 Non-indigenous25.921.521.319.617.9 Total 27.422.922.220.719.4
www.melbourneinstitute.com Homelessness rates by housing and labour market characteristics
www.melbourneinstitute.com Homelessness and geographic mobility Homeless rate Entry rate Exit rate N Remained in same area (‘stayers’) 22.214.171.124,766 Moved across areas (‘movers’) 28.921.655.9730 Total 19.08.742.05,496
www.melbourneinstitute.com Homelessness, ‘stayers’ Homeless rate Entry rate Exit rateN Housing market high rent area21.66.930.31,270 medium rent area126.96.36.199,814 low rent area17.78.343.61,682 Labour market high unemployment area16.97.843.01,773 medium unemployment area188.8.131.52,455 low unemployment area184.108.40.206,538 Total didn’t move across areas220.127.116.11,766
www.melbourneinstitute.com Homelessness, ‘movers’ Homeless rate Entry rate Exit rate N Housing market Moved from lower ranked rent area30.822.152.4247 Moved from similarly ranked rent area28.119.347.1196 Moved from higher ranked rent area27.923.163.4287 Labour market Moved from lower ranked unemployment area30.720.953.1261 Moved from similarly ranked unemployment area23.616.958.5195 Moved from higher ranked unemployment area31.025.957.6274 Total moved28.921.655.9730
www.melbourneinstitute.com Tentative conclusions Housing markets matter for those at-risk No clear relationship with local labour markets Further research examining whether characteristics (observed and unobserved) of individuals explain patterns Interact individual risk factors and structural factors (e.g. housing and labour markets) –As those not at-risk won’t become homeless –As persons with certain risk factors might be more prone to homelessness if facing adverse structural factors
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