Preconditions for Employment for Roma: Ethnically sensitive data collection

1
Preconditions for Employment for
RomaEthnically sensitive data collection

• Susanne Milcher
• Specialist, Poverty and Economic Development
• UNDP Regional Centre
• Bratislava
• (25 April 2005)

2
Outline

• General problems with ethnic data
• Why is ethnic data needed?
• Data collection systems
• Ethnic data in practice
• Policy application
• Ideas for Guidelines

3
Problems with ethnic 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
• Absence of ethnic data creates opportunities to
  misuse and misinterpret data deficits
• Data might still be collected and used with
  negative effects (i.e. criminal justice)

4
Why is ethnic data needed?

• Measurement of discrimination (indirect) or equal
  treatment
• - data recording and collection
• - indicators demonstrating differentials and
  assessment of their extent and variations (How
  much worse is the status and what are the
  specific characteristics of their status)
• - set quantified objectives for promoting
  equality

5
Why is ethnic data needed?

• Reliable quality quantitative data is a
  necessary precondition both for understanding the
  underlying causes of the differentials and
  addressing them adequately by 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

6
How to collect ethnic data?

• 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

7
Data collection systems

• Data protection of sensitive data
• (fear of misuse and discrimination)
• - but it is needed in order to identify
  discrimination and its causes
• - identify particular disadvantages and
  obstacles that Roma in labour market face
  supply of data is absolutely needed to dispel the
  deep-seated myths
• Instruments (census, surveys, registries)
• - understate Roma, costly and difficult
  sampling, unreliable and imperfect data

8
Roma Unemployment (ILO definition)
Source UNDP, Vulnerable groups survey 2004.
9
Serbia Unemployment rate
Source UNDP, Vulnerable groups survey 2004.
10
Macedonia Unemployment rate
Source UNDP, Vulnerable groups survey 2004.
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Determinants of unemployment
Unemployed Roma in specific countries as a percentage of the population, organised by selected categories (2004) Unemployed Roma in specific countries as a percentage of the population, organised by selected categories (2004) Unemployed Roma in specific countries as a percentage of the population, organised by selected categories (2004) Unemployed Roma in specific countries as a percentage of the population, organised by selected categories (2004) Unemployed Roma in specific countries as a percentage of the population, organised by selected categories (2004)
Characteristics unemployed unemployed unemployed unemployed
Bulgaria Czech Republic Hungary Romania
Youth (15-24) 56 40 37 46
Prime age adults (25-44) 35 28 10 25
Older adults (45-59) 33 24 71 28
Elementary or less 47 40 16 37
Primary 40 23 18 35
Secondary 28 15 10 20
University n.a. 23 33 25
Source UNDP, Vulnerable groups survey 2004.
12
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?

13
Ideas for Guidelines

• Need capacity of statistical institutions to
  provide necessary guarantees
• Legal framework in order to create a balance
  between need to identify discrimination or status
  differences and protection of privacy (individual
  data) high level safeguards are a precondition
• Use existing data collection systems, using a
  common approach (harmonisation)
• Cooperation and partnership between data
  producers and users
• Standards for collected data (reliability,
  consistency, usefulness)

14
Ideas for Guidelines

• Based on recommendations of the first Experts
  Group meeting, July 2004
• The Census should be the instrument to collect
  ethnic data but
• Method improvement partnership with local
  communities, instructions
• Self-Identification Multiple choice question on
  ethnicity adding question on religion, language,
  partners ethnicity or country of birth origin
• HBS/LFS can only partially be used to collect
  ethnic data
• Better than administrative registries
• Sampling difficult

15
Thank you!

• Bratislava Regional Center
• 35 Grosslingova
• 81109 Bratislava, Slovak Republic
• 421 2 59337 111
• www.undp.sk
• http//roma.undp.sk
• http//vulnerability.undp.sk