Quantitative data collection on the status of Roma in SEE and CEE:
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Quantitative data collection on the status of Roma in SEE and CEE: Methodology, Purpose, and Policy Application. Susanne Milcher Specialist, Poverty and Economic Development UNDP Regional Centre Bratislava (17 September 2004). Outline. General problems with ethnic data

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Susanne Milcher Specialist, Poverty and Economic Development UNDP Regional Centre Bratislava

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Susanne milcher specialist poverty and economic development undp regional centre bratislava

Quantitative data collection on the status of Roma in SEE and CEE:Methodology, Purpose, and Policy Application

Susanne Milcher

Specialist, Poverty and Economic Development

UNDP Regional Centre


(17 September 2004)



  • General problems with ethnic data

  • The baseline survey methodology

  • Policy application

  • Future steps

Problems with relevant data

Problems with relevant data

  • Governments reluctant to collect

    • Political considerations

    • Constitutional constraints

  • Constituencies reluctant to share

    • Desire to avoid discrimination and stigmatization

    • Desire to keep distance from the state

      As a result:

  • Opportunities to misuse and misinterpret data deficits

  • But all aware that data is necessary

Undp approach to the issue

UNDP approach to the issue

Reliable quality quantitative data is a necessary

precondition for relevant policies. It means data,

which is:

  • Relevant, adequately reflecting reality

  • Comparable – both between countries and with majority populations (control group) in individual countries – over time

  • Respecting privacy – making sure will not be misused, individual is protected against discrimination

How to get there the survey

How to get there? The survey

  • Problems are of technical, methodological and legal nature and specific problems require specific approaches

  • Clear division of roles between international and national actors necessary in the short, mid and long run (phase-out strategy)

  • Link to MDGs monitoring (baseline)

How to get there

How to get there?

  • Relevancy – related primarily to communities involvement in data collection (Roma interviewers where possible, assistant interviewers in other cases)

  • Comparability – applying consistent methodologies in different countries following the format HBS and LFS

  • Include majority boosters

  • Respecting privacy – not using registry data

Previous experience

Previous experience

  • Regional UNDP/ILO large scale survey on Roma in five Central and Eastern European (CEE) countries conducted in 2001

  • Situation of Roma from a ‘human development’ perspective

  • “How much” worse and specific characteristics of their status

  • Answering these specific and concrete questions in quantitative figures is a necessary precondition both for understanding the underlying causes and addressing them adequately

Roma poverty profiles

Roma: poverty profiles

Roma deprivation indicators of people lacking access to

Roma: Deprivation indicators (% of people lacking access to)

Roma deprivation indicators of people lacking access to1

Roma: Deprivation indicators (% of people lacking access to)

Roma unemployment ilo definition

Roma: Unemployment (ILO definition)

The survey i

The survey I

  • Supposed to provide base-line data for the “Decade” progress monitoring and for NTL policy purposes

  • Covers all countries in SEE and CEE with sizeable Roma minorities (“Decade +”)

  • Where relevant, has IDPs and refugees boosters

  • Will be the basis of a “regional vulnerability report”

  • Could be used as a pilot for similar data collection exercises in the region

The survey ii

The survey II

  • The unit of analysis – household

  • Main interviewee – head of the household

  • Universe studied – households in Roma settlements

  • Roma settlements – municipalities or neighborhoods with high concentration of Roma

  • Territorial unit – municipalities with share of Roma population equal or above the NTL average as registered by the census

The sampling model assumptions

The sampling model assumptions

  • Census understate absolute numbers but reflect the structure and distribution (“where those people are?”)

  • The major disparities visible at the level of municipalities

  • Comparability with the “majority in proximity” more important than with national average

  • Majority boosters – a “benchmark” sample for comparisons with non-Roma in similar socioeconomic environment

Inevitable impediments

Inevitable impediments

  • Sample may be under-representing integrated Roma

  • Majority population in proximity may not be sufficient for constructing a booster

  • Concentrated Roma neighborhood may still constitute a share lower than the NTL average

  • Data not representative for sub-grouping

What shall the survey provide

What shall the survey provide?

  • Household representative information, “census-type” allowing approximations for

    • Poverty rates and depth

    • Levels and sources of income

    • Educational attainment, completion rates, enrollment rate and functional literacy

    • General picture of health status and access to health services

    • Dwellings characteristics (water, sanitation) for deprivation indicators

  • All this - disaggregated by age, sex, income status of the household and sub-national level

Dose of realism the inevitable constraints

Dose of realism (the inevitable constraints)

  • Not all indicators are possible to be monitored or disaggregated

  • Data (as any data perhaps) – still approximation and should be used as complementary to other statistics

  • Cross-country comparability will be limited (if necessary at all)

Time frame


  • Completed sampling methodology and questionnaire

  • August/September – translating, back translation and testing of the questionnaire; sampling

  • End of August: identification of assistant-interviewers and first training (Sofia)

  • October: field-work

  • November: data available

  • First quarter 2005 “Vulnerability Assessment”

Policy application

Policy application

  • Only based on quantitative data can the actors involved (governments, donors, implementing partners) outline priorities and measure progress

  • Disaggregated quantitative data is a precondition for relevant national-level policies for sustainable inclusion of vulnerable groups and Roma in particular

  • Monitoring and evaluation of national-level policies, what impact has been achieved?

Future steps and possible cooperation

Future steps and possible cooperation

  • Improve methodologies for vulnerability analysis to establish disaggregated data collection capacities at the country level in 2-3 years

  • Work with National Statistical Offices on practical projects on data disaggregation

  • Elaborate possible approaches to overcome legal barriers

  • Encourage and coordinate advocacy campaign for new approach to “group-related” data, incl. ethnic groups

Links to other roma related initiatives

Links to other Roma-related initiatives

  • Follow up to first regional report“Avoiding the Dependency Trap”

  • Decade of Roma Inclusion baseline and monitoring

  • Measuring the progress at national level (Czech Republic and Hungary)

  • WB “Living Standards” assessment

  • Roma Development Opportunities Web-site, http://roma.undp.sk

Thank you

Thank you!

Bratislava Regional Center

35 Grosslingova

81109 Bratislava, Slovak Republic

+421 2 59337 111




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