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 ?

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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)

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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

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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

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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

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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

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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)

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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

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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





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





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

Government & Nonprofit

Making Homeless People Visible in the EU-SILC Surveys