Katarina Mathernova
16 May 2011


The right thing to do!

Political opportunity – greater awareness; political momentum at the EU level – April 5 th
Communication

Makes economic sense – World Bank study on
Benefits of Roma Inclusion


4 country study: Bulgaria, Czech Republic, Romania and Serbia

Majority populations in these countries are aging. Roma share of new labor market entrants is high and growing

Large employment gap. Biggest driver is the large educational gap, especially at the secondary level

Closing labor market gap can increase national incomes by up to Euro 5.5 billion and tax revenues by Euro 1.5 billion in these 4 countries

Study – Roma Inclusion: An Economic
Opportunity
Focus: Inclusion in Employment
Countries: Bulgaria, Czech Republic, Romania, Serbia
Quantitative analysis: 7 household surveys
Qualitative analysis: interviews with 222 stakeholders

Study: Four key messages
* Roma inclusion is smart economics
* Roma want to contribute and have the potential to do so
* There is knowledge about what needs to be addressed
* Resources are available

80
60
40
Roma are much less likely to be working than non-Roma
100
% Employed
70
41
56
40
63
50 51
36
20
0
Bulgaria Czech Republic Romania
Non-Roma Roma
Serbia

20
0
80
60
40
Roma with jobs earn much less than non-
Roma
100
Relative average wages: majority is 100%
100 100 100 100
69
43
39
51
Bulgaria Czech Republic Romania
Non-Roma Roma
Serbia

Young Roma are entering labor markets at much higher rates than aging majority populations
% Population 0-15 years old

2500
2000
1500
1000
500
0
Equal labor market opportunities would generate billions of euros annually in extra output
Euros
3000
2 980
526
1 070
367
887
252
1 048
Bulgaria (2007) Czech Republic*
(2008)
Lower population est.
Romania (2008)
Higher population est.
Serbia (2007)

Equal labor market opportunities would generate fiscal benefits of hundreds of millions of euros annually
Euros
700
600
500
400
300
200
100
0
128
260 260
Bulgaria (2007) Czech Republic*
(2008)
Lower population est.
202
675
Romania (2008)
Higher population est.
62
257
Serbia (2007)

Fiscal benefits are many times larger than the public spending on education
•
Assume it would cost 50% child more per Roma
•
Assume Roma currently complete primary and 10% completes secondary
•
Assume no Roma attends pre-primary or tertiary
•
Fiscal benefits would be >3 times the needed resources to bridge education gap

Facts do not accord with common perceptions:
Roma want to work but cannot find jobs
% Working age population participating in labor force
100
100
85
79
84
80 75
80
68
70
72 68
61
59
60
60
49
40
40
28
20
20
0
Bulgaria Czech Romania Serbia
Republic
Male LFP
Roma
58
37
55
40
0
Bulgaria Czech Romania Serbia
Republic
Female LFP
Roma

80
60
40
Facts do not accord with common perceptions: vast majority of Roma do not depend on social assistance
% Households receiving social assistance
100
25
16
20
0
12
Bulgaria Romania
Proportion of population (%)
Serbia

Education facts accord with perceptions: the vast majority of Roma do not have a secondary education or higher
% Working age population with secondary and/or vocational
100
87
80
80 75
77
60
40
20
20
13 12 13
0
Bulgaria Czech Republic Romania
Majority Group Roma
Serbia

Roma Inclusion Requires a Multi-
Dimensional Approach
Priority areas include:
• Employment activation policies
• Ensuring equal education opportunities
• Addressing housing inequities
• Closing health disparities

Katarina Mathernova
16 May 2011

LAU 1 level (‘nuts 4’) – 262 municipalities (2005)







East Asia: Cambodia, China, Indonesia, Laos, Papua New
Guinea, Philippines, Thailand, Vietnam
South Asia: Bangladesh, India, Nepal, Sri Lanka
Latin America: Bolivia, Brazil, Chile, Colombia, Dominica,
Ecuador, Guatemala, Honduras, Mexico, Nicaragua,
Panama, Paraguay, Peru
Africa: Burkina Faso, Cape Verde, Central African
Republic, Cote d’Ivoire, Gabon, Gambia, Guinea, Ghana,
Kenya, Madagascar, Malawi, Mali, Mauritania,
Mozambique, Namibia, Niger, Rwanda, Senegal, Sierra
Leone, South Africa, Tanzania, Uganda, Zambia,
North Africa: Morocco, Tunesia, Egypt, Yemen, Jordan
Eastern Europe and FSU: Albania, Azerbaijan, Bulgaria,
Kazakhstan, Tajikistan


In summary:
Household survey like EU-SILC have breadth of indicators, but sample sizes too small to be representative for local area units

Population censuses do allow small areas calculations but frequently lack breadth of indicators necessary to calculate main poverty indicators
Source: “EU legislation on the 2011 Population and Housing Censuses” (Eurostat
2011, ISSN 1977-0375)

Background characteristics unique to EU-
SILC
Common Household Background
Characteristics
EU-SILC or other detailed survey
Step 1
Household Welfare
Indicator(s) such as at-risk-of-poverty in
EU-SILC
Step 0
Common Household Background
Characteristics
National Population Census
Step 2
Household Welfare
Indicator(s) such as at-risk-of-poverty not in census
POVERTY MAP(S)

LAU 1 level (‘nuts 4’) – 262 municipalities (2005)


Main Findings
Considerable variation in poverty levels across municipalities: 3%-40% of individuals

Considerable variation in poverty levels across municipalities within the same district

Poorest areas characterized by relatively higher shares of ethnic minorities (Roma and Turk households)

Poorest areas characterized by lacking in human capital endowment and in infrastructure


Poverty maps can be very useful tool to target poorest areas with inclusion programs

Poverty maps have been implemented around the world. If data are available, production of poverty maps takes several months

Policy relevance and adoption of poverty maps enhanced through considerable outreach and capacity building

Population censuses being implemented throughout the EU in 2011 and availability of annual EU-SILC survey data are promising