What is it to be Roma in the EU?

Approaches to data and what data say

INSTAT/UNAR/ANCI conference, 6 February 2017

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Outline• Why do we need data disaggregated by ethnicity in the

case of Roma?• What are the challenges in generating such data and how

they can be addressed?• Looking into the future

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With EU enlargement, vast resources have been made available for Roma integration

…but are they getting us closer to desired goal? FRA data suggest ‘no’

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Employment

Fewer than one out of three Roma are reported to be in paid employment

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Picture: Roma Realities – Decade 2005-2015, SDC and the World Bank

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Youth

On average, 63% of young Roma are neither working,

nor are in education or training

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Picture: FRA, LERI project locality (Slovakia)

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Poverty

80 % of Roma live below the at-risk-of-poverty threshold

Picture: Roma Realities – Decade 2005-2015, SDC and the World Bank

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Almost half of Roma in the age of upper secondary education do not go to schoolwith many engaged in income generation

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Picture: Roma Realities – Decade 2005-2015, SDC and the World Bank

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Housing

Every third Roma lives in housing without tap water

One in 10 live in housing without electricity

9Picture: Roma Realities – Decade 2005-2015, SDC and the World Bank

Health

About one in three Roma indicate that their everyday activities have been limited in some way by health problems

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10Picture: FRA, LERI project locality (Finland)

Rights awareness

Almost a third of theRoma surveyed do not know of

any law prohibiting discrimination, and most (82 %) do not know of

any organisation offering support to

discrimination victims

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Going beyond news headlines• Data for structure indicators• Data for process indicators

Roma strategy (national level) Program level (OPs and other) Project level

• Data for outcome indicators What control group to use

The purpose determines the data and the data collection tools

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…all this is based on data. How we get data?• First step: determine what kind of data we need• Second step: define the population (the ‘universe of

study’) – along – Ethnic criteria?– Socio-economic criteria?– Territorial?

• Method of identification– Self-identification?– Third party identification

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Using data: assessing the magnitude of the gap

Source: FRA, EU MIDIS II surveyChildren aged between 4 years and the starting age of compulsory education who participate in early childhood education

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Roma aged 6-24 years by educational level they attend (%)

Source: FRA, EU MIDIS II survey

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Looking to the future• Opportunities and risks related to ‘big data’ and IT technologies• A degree of compromise between statistical rigor, political

dimensions and policy needs is desirable• Cascading approach to data collection.

– Mainstreaming data collection in the National Statistical systems is a first best option. If it is not feasible,• Second best might work. If it is not feasible,

– Third best would be needed

• Whatever the option, consensus on the definition of the universe is needed – for the specific purpose of the data collection exercise– Or modifying the horizontal social inclusion measures so that they do

reach Roma?

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Next stage – 18 Member States• Countries not covered by EU MIDIS II differ significantly• Italy – several open issues

– Which groups to target (autochthonous only or also citizens of other member states)

– What is the purpose of the data collection – to generate information for process or for outcome indicators

– Which approach to take regarding the sampling frames (if data collection is to be done through a survey)

fra.europa.eu

The pictures used are from:FRA ‘Local Engagement in Roma Inclusion’ project localities

SDC and the World Bank. (2015). Decade 2005-2015

Lívia Mašlárová. (2014). Dejiny Rómov

Roma das unbekannte Volk. Wien-Köln-Weimar, 1994

For more information you can contact us at

romaprogramme@fra.europa.eu