Roma poverty and deprivation: the need for multidimensional measures Andrey Ivanov, FRA 1

Outline Why monitoring progress on Roma inclusion is important? What are the myths around data and what are the available data sources? What the available data say – and what they do not say? How multidimensional poverty monitoring might help? 2

The EU: ‘cascading’ involvement in Roma integration (1) The European Commission Communications –Framing the issue in line with the Inclusive Growth priority of the EU 2020 strategy; calling for National Roma Integration Strategies and clear local-level focus with active role of Roma civil society; assessing the first drafts of the strategies and their results. The European Council –2013 Council Recommendation on effective Roma integration measures in the Member States and on monitoring and evaluation 3

The EU: ‘cascading’ involvement in Roma integration (2) European Parliament and the Council 2013: Ring-fence allocation of 20 % of the total ESF resources for “promoting social inclusion, combating poverty and any discrimination” and Ex-ante conditionalities for improvement of the situation of marginalised communities such as the Roma –the implementation of a National Strategic Policy Framework for Poverty Reduction (Conditionality 9.1) –a national Roma Inclusion Strategic Policy Framework (Conditionality 9.2).

Three myths about data on Roma 1.There is no data, so we don’t know A number of countries use ethnic markers on censuses and standardized European social surveys Territorial mapping Custom surveys 2.There is no need of data because we know how bad it is anyway It is important to know not just how bad it is – but most of all, why? 3.We might need but it can’t be collected because of legal constraints Constraints exist but they are overestimated

Measuring progress Progress of who? –Defining the target group is misleadingly –The outcome differs depending on the approach one takes Research (historical or ethnological) Pragmatic (policy-driven) Progress in what – integration vs. inclusion Measuring how? What indicators to populate with the data? –Input-output-outcome –Structure-process-outcome 6

Data examples: census, Bulgaria (1) Gross enrolment rate in primary, secondary and tertiary educational levels (share of the respective age group) 7 Source: NSI, census 2011

Data examples: census, Bulgaria (2) 8 Highest achieved educational level (population aged 7 and above who are not in education) Source: NSI, census 2011

Data examples: census, Bulgaria (3) 9 Employment, unemployment and activity rates Source: NSI, census 2011

Data examples: LFS, Hungary Labour market participation of Roma and Non- Roma, Source: LFS, 2013

Data examples: LFS, Hungary (2) Security of employment among Roma and Non- Roma, Source: LFS, 2013

Data examples: custom surveys (FRA, UNDP/WB/EC) Data derived from representative surveys in 11 EU Member States (FR, ES, PT, IT, PL, EL,CZ, SK, BG, RO, HU) Two samples –Roma –Their non-Roma neighbours Levels of comparability: –within groups, –between groups, –with national averages (on major indicators) 12

Population at risk of poverty Population in household with equivalent expenditure below 60% of the national median, in %) Sources: FRA Roma survey 2011, EUROSTAT 2011

Structure of household income, 2011 Roma Non-Roma Source: UNDP/WB/EC Roma survey 2011 The share of total work-related incomes (from “employment” and “other labour related activity”) is remarkably similar between both groups. The same applies for social transfers with the only difference in pensions (higher share among non-Roma) and social assistance (higher share among non-Roma)

Structure of household expenditures, 2011 Non-Roma Source: UNDP/WB/EC Roma survey 2011 Roma The income structure of Roma households is dominated by expenditure on food – typical for developing countries

25 to 64 who completed at least upper secondary education (vocational or general) (%) Sources: FRA Roma survey LFS 2011 Attainment rates

Source: FRA Roma survey 2011 School (un)attendance Respondents aged 16 and above who have never been to school (%) …or in other words – who have not had the chance of exercising their fundamental right to education

Malnutrition Share of persons living in households in which someone went hungry at least once last month because the family couldn’t afford buying food Source: FRA Roma survey 2011 High share of Roma families cannot exercise a fundamental right of being free from hunger

Unemployment rates by gender and ethnicity 19 Source: UNDP/WB/EC Roma survey 2011, EUROSTAT

Discrimination and prejudice Experience of discrimination in employment in the last five years because of being Roma in the 5 EU Member States (%) 20 Source: FRA Roma survey 2011

21 Having the data is just the first step. Making sense of it (and using it for policy purposes) does not come automatically We have the data… Now what?

Roma Multidimensional poverty index Follows Alkire and Foster (2007) methodology Structured in two areas a.Human capabilities b.Material wellbeing Six equally weighted dimensions a.1. Basic rights a.2. Health a.3. Education b.1. Housing b.2. Standard of living b.3. Employment 12 indicators (two for each dimension) 22

‘Human capabilities’ area DimensionIndicatorsCriterion of deprivation and threshold Level of observ. Basic rights Civil status Having an ID – yes/no (personal document, birth certificate etc.) I Discrimination HH member lives in a HH where a member has been discriminated against while looking for a job P Health Disability statusA household member having a disability – yes/noI Limited access to medical services Any HH member living in a HH responding "yes" to the question "were there any periods in the past 12 months when you couldn’t visit a doctor when you needed?” P Education Highest completed education For adults: any HH member above schooling age who hasn’t completed primary education or lower secondary For children: children in school age who are not in school I Self-declared illiteracy rateAny HH member stated as unable to read and writeI 23

‘Material wellbeing’ area DimensionIndicatorsCriterion of deprivation and threshold Level of observ. Housing Access to basic infrastructure A composite indicator –any HH member living in a HH without two of the three (toilet or bathroom inside the house; running water; electricity) H Shares of the population not having access to secure housing Any HH member living in "ruined houses" or "slums" H Standard of living Extreme poverty Any HH member living in a HH that experienced that in the past month somebody ever went to bed hungry because they could not afford enough food for them H Access to various HH amenities Any HH member living in a HH, which doesn't possess four of six categories falling in the "Material deprivation" index I Employment Unemployment Any HH member living in a household with none of the adult HH members employed (16+). H Lack of working experience Any HH member living in a HH in which the HH head or his/her spouse has no working experience H 24

Measuring poverty – but which exactly? Source: UNDP/WB/EC Roma survey 2011

26

27

28

Composition of Roma poverty (BG, RO) Non-severe and severe poverty rates bars left scale) and the value of MPI (right scale) 29 Source: UNDP/WB/EC Roma survey 2011

Multidimensional poverty (BG, RO) Change in multidimensional poverty rates of Roma and non-Roma 30 Sources: UNDP Roma survey 2004; UNDP/WB/EC Roma survey 2011

Structure of deprivations Changes in multidimensional poverty deprivations structure of Roma in BG and RO, Source: UNDP/WB/EC Roma survey 2011

Quantitative data is not enough Data outlines the status and rarely the determinants Figures are rarely put in their specific context We keep measuring what is measurable The missing dimensions –Agency –Fundamental rights –Discrimination 32

The missing dimensions: aspirations Educational aspirations and multidimensional poverty 33 Source: UNDP/WB/EC Roma survey 2011

Conclusions - data Data from different sources have different strengths and weaknesses and should be used in complementary manner Including ethnic identifiers makes possible –For censuses to provide reliable and robust data for monitoring long-term changes –For standardized European surveys to yield data with higher frequency Custom sample surveys can –Fill the gap in cases when applying ethnic identifiers is not possible and –Provide comparability across countries 34

Conclusions - indicators Multidimensional poverty concept reflects better the specific challenges of Roma inclusion It yields lower poverty rates but reflects the reality better From policy perspective, it allows understanding better the drivers of poverty Important dimensions (namely agency and aspirations) are still not sufficiently covered –An area that might be addressed through thematic modules in the standardized European Surveys 35

Thank you for your attention! For more information you can contact us at