Making Homeless People Visible in the EU-SILC Surveys

9th European Research Conference
Homelessness in Times of Crisis
Warsaw, Friday 19th September 2014
Making homeless people visible in the EU-SILC surveys
Ides Nicaise & Ingrid Schockaert University of Leuven (HIVA)
Research commissioned by the Belgian Combat Poverty Service and sponsored by BELSPO

SILC-CUT project
• EU-SILC as key data source for EU-wide poverty statistics…
• …and policies (Europe 2020 headline target)
• Problem: how representative is EU- SILC for AROPE ?
2-10-2014
2

Objectives of the research
Examine representativeness of EU-SILC for groups with enhanced poverty risks in Belgium
Sampling issues
Non-response and attrition (+ prevention strategies)
Examine feasibility of ‘satellite surveys’ among hard- to-survey (H2S) groups in Belgium
adjusted questionnaires
Pilot surveys among two H2S groups (homeless people and undocumented immigrants)
2-10-2014
3

Homeless illustrate sampling issues
Excluded from sample framework
Undocumented (illegal) immigrants
Collective households (prisons, institutions, convents…)
Asylum seekers ?
People who do not live in their legal residence
Homeless people (even those having a ‘reference address’)
Itinerant groups (travellers, …)
People living permanently on campings
2-10-2014
4

Experimental satellite surveys
Why homeless people and undocumented immigrants ?
‘obscurity’
Size of these groups
Extreme poverty
Why ‘statistical survey’ ?
Comparison of statistical profile with other groups
Monitoring of specific aspects of living conditions
2-10-2014
5

Definition of ‘homeless’
See ETHOS definition, categories 1 & 2
Roofless (rough sleepers)
Houseless (living in shelters)

Experimental satellite surveys (ctd)
Overall strategy
Indirect sampling in collaboration with social services and advocacy groups
Adapted questionnaire design
Close monitoring of interviewers (carried out by specialised survey team)
Preliminary statistical analysis of data
Feedback to intermediaries and policy makers
2-10-2014
7

Sampling and response
Stratified sample based on available (scarce) information
Extensive negotiation with intermediaries from social services (= gatekeepers)
Compromises between scientific and pragmatic criteria (e.g. mental health issues, peer pressure…)
Snowball method rather ineffective
Undocumented immigrants very hard to reach (language x fear)
Remaining response bias unavoidable
2-10-2014
8

Some key findings
High AROP rates (72% among homeless, 96% among undocumented immigrants) with extreme financial deprivation among the latter. => Lack of effectiveness of guaranteed minimum income and social assistance scheme
High proportions of women with children (32% among homeless, 53% among undocumented migrants)
Deprivation rates = 100% in both groups – with extreme hardship among rough sleepers (no access to potable water, toilet or shower in their place of residence)
2-10-2014
9

Some key findings (ctd)
Severe housing problems among undocumented immigrants (overcrowding, exploitation, lack of basic amenities)
Severe health problems (24% among homeless, 37% among undocumented migrants). Mainly nervous / psychological distress (lack of sleep, anxiety, loneliness, addiction…). Non-use of medical services for financial reasons
2-10-2014
10

Conclusions
Representativeness of surveys w.r.t. poverty should be improved
At level of sampling (prior identification of H2R groups
At level of research design (adapted questionnaires, anticipation of exceptional situations)
At level of data collection (specific subsamples, appropriate survey methods, interviewer training, anticipation of language barriers)
At level of data treatment (re-weighting)

Conclusions (continued)
Surveys about living conditions of specific disadvantaged groups are useful and feasible:
•Hard figures as a complement to ethnographic studies
•Comparability between subgroups, ‘average’ poor and population
•Comparisons between EU countries and across time
Yet the data collection is difficult => preconditions
•Partnership between researchers and social services
•Well-trained and supported survey team
•considérable time investment
•Realistic sampling procedure (access <=> representativeness)
•Simplified questionnaires + extensive guidelines

www.inclusivegrowth.be
13
Conclusions (continued) Suggestions w.r.t. EU-SILC satellite surveys
Co-ordinated across member states
Rotating sampling plan
No (rotating) panel design
fixed sample size for each group
Simplified questionnaires + tailored interview modules (e.g. administrative situation of undocumented migrants; hygiene conditions of homeless people…)
Title/date

14
Conclusions (continued) Suggestions w.r.t. EU-SILC satellite surveys example of sampling plan
GROUPS
Year T
Year T+1
Year T+2
Year T+3
Year T+4
Year T+5
Year T+6
Year T+6
Year T+6
1 & 2
X
X
3
X
X
4 & 5
X
X
6
X
X
7
X
…
Title/date

15
References
Nicaise, I., Schockaert, I., The hard-to-reach among the poor in Europe: lessons from Eurostat’s EU-SILC survey in Belgium, in: R. Tourangeau et al. (2014), Hard-to-survey populations, Cambr. Univ. Press (ch. 26)
Schockaert, I., Morissens, A., Cincinnato, S., Nicaise, I., Armoede tussen de plooien. Aanvullingen en correcties op de EU-SILC voor verborgen groepen armen, Leuven: HIVA, 2012, 225p
Title/date

Making Homeless People Visible in the EU-SILC Surveys

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