Extending EU-SILC to homeless people: the Belgian experience Ides - - PowerPoint PPT Presentation

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Extending EU-SILC to homeless people: the Belgian experience Ides - - PowerPoint PPT Presentation

Sep 21, 2023 41 likes •132 views

Extending EU-SILC to homeless people: the Belgian experience Ides Nicaise, KU Leuven Research commissioned by the Belgian Combat Poverty Service and sponsored by BELSPO This project has received funding from the European Unions Seventh

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This project has received funding from the European Union’s Seventh Programme for Research, Technological Development and Demonstration under Grant Agreement No 312691

Extending EU-SILC to homeless people: the Belgian experience

Ides Nicaise, KU Leuven

Research commissioned by the Belgian Combat Poverty Service and sponsored by BELSPO

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www.inclusivegrowth.be

Homeless people as a H2S group in EU-SILC

Why homeless people ? (several H2S groups identified)

  • ‘obscurity’
  • Size of the group
  • Extreme poverty

Why a ‘statistical survey’ ?

  • Estimation of bias in poverty rates based on EU-SILC
  • Comparison of statistical profile with other groups
  • Possibility of international comparison
  • Monitoring of living conditions across time

30-5-2016

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www.inclusivegrowth.be

Homeless people as a H2S group

  • Hard-to-sample: absence of (direct) sampling framework
  • (Hard-to-identify: ETHOS typology)
  • (Hard-to-contact: not really)
  • (Hard-to-persuade: no – rather ‘gatekeepers’)
  • Hard-to-interview:

– Low literacy – mental illness / disorders – complexity of living conditions (different interpretations of basic concepts: household, work, income, …)

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www.inclusivegrowth.be

Overall strategy of the survey

  • Indirect (two-stage) 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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www.inclusivegrowth.be

Sampling and response

  • Sample stratified by region, gender and age group

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
  • Remaining response bias unavoidable

30-5-2016

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www.inclusivegrowth.be

Strata and response (target 250 / reached 275)

Flanders Brussels Wallonia 91 /141 71 / 68 88 / 68 Male Female Male Female Male Female 61 / 89 30 /52 57 /41 14 / 27 64 / 38 24 / 30 Roofless Homeless Roofless Homeless Roofless Homeless 13 / 19 78 / 122 11/19 60 / 49 13 / 26 75 / 42 < 30 30-50 >50 < 30 30-50 >50. < 30 30-50 >50

47 / 50 31 / 66 13 / 21 30 / 15 29 / 37 12 / 16 37 / 17 36 / 39 15/10

Selectieve (non-)respons - DTL

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www.inclusivegrowth.be

Some key findings

  • High AROP rates (72%)

=> Lack of effectiveness of guaranteed minimum income and social assistance scheme => surprises: e.g. one home-owner

  • Deprivation rates = 100% – with extreme hardship among

rough sleepers (no access to potable water, toilet or shower in their place of residence)

  • High proportions of women with children (32%)

30-5-2016

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www.inclusivegrowth.be

Some key findings (ctd)

  • Severe health problems (24%). Mainly nervous /

psychological distress (lack of sleep, anxiety, loneliness, addiction…). Non-use of medical services for financial reasons

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TÁRKI Social Research Institute Inc. (HU) Amsterdam Institute for Advanced labour Studies, Universiteit van Amsterdam (NL) The Swedish Institute for Social Research, Stockholms Universitet (SE) Fachbereich IV, Wirtschafts- und Sozialstatistik, Universität Trier (DE) Centre d’Etudis Demogràfics, Campus de la Universitat Autònoma de Barcelona (ES) Centre d’Etudes de Population, de Pauvreté et de Politiques Socio-Economiques (LU) Centre for Social Policy, Universiteit Antwerpen (BE) Institute for Social & Economic Research, University of Essex (UK) Bremen International Graduate School of Social Sciences, Universität Bremen (DE) Department of Dynamics of Organisations of Work, Centre d’Etudes de l’Emploi (FR) The Centre for European Policy Studies (BE) Dipartimento di Economica e Menagement, Università di Pisa (IT) Social Statistics Division, University of Southampton (UK) Luxembourg Income Study, asbl (LU) WageIndicator Foundation (NL) School of Social Sciences, The University of Manchester (UK)

Partners Co-ordinator

Inclusive Growth Research Infrastructure Diffusion Contract No 312691 For further information about the InGRID project, please contact inclusive.growth@kuleuven.be www.inclusivegrowth.be p/a HIVA – Research Institute for Work and Society Parkstraat 47 box 5300 3000 Leuven Belgium

Guy Van Gyes Monique Ramioul

InGRID

NICAISE I., SCHOCKAERT I., The hard-to-reach among the poor in Europe: lessons from Eurostat's EU-SILC survey in Belgium, in TOURANGEAU R. EDWARDS B., JOHNSON T., WOLTER K., BATES N. (eds., 2014), Hard-to- survey populations, Cambridge University Press, p.1246-1279

See also session on EU-SILC Thursday afternoon