Roma Inclusion: An Economic Opportunity

WHY SHOULD GOVERNMENTS DO SOMETHING?

Katarina Mathernova,World Bank

16 May 2011

The right thing to do!

Political opportunity – greater awareness; political momentum at the EU level – April 5th Communication

Makes economic sense – World Bank study on Benefits of Roma Inclusion

WHY SHOULD GOVERNMENTS DO SOMETHING about Roma

inclusion?

Economic argument for

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

Economic Benefits of Roma Inclusion (World Bank, 2010)

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

Roma are much less likely to be working than non-Roma

Bulgaria Czech Republic Romania Serbia0

20

40

60

80

100

70

5663

51

41 40

50

36

Non-Roma Roma

% Employed

Roma with jobs earn much less than non-Roma

Bulgaria Czech Republic Romania Serbia0

20

40

60

80

100100 100 100 100

69

4339

51

Non-Roma Roma

Relative average wages: majority is 100%

Young Roma are entering labor markets at much higher rates than aging majority populations

% Population 0-15 years old

Equal labor market opportunities would generate billions of euros annually in extra output

Bulgaria (2007) Czech Republic* (2008)

Romania (2008) Serbia (2007)0

500

1000

1500

2000

2500

3000

526367

887

252

1,070

2,980

1,048

Lower population est. Higher population est.

Euros

Equal labor market opportunities would generate fiscal benefits of hundreds of millions of euros annually

Bulgaria (2007) Czech Republic* (2008)

Romania (2008) Serbia (2007)0

100

200

300

400

500

600

700

128

260202

62

260

675

257

Lower population est. Higher population est.

Euros

Fiscal benefits are many times larger than the public spending on education

• Assume it would cost 50% more per Roma child• 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

Male LFP Female LFP

Bulgaria Czech Republic

Romania Serbia0

20

40

60

80

100

79

6875

70

85

61

84

72

Majority group Roma

Bulgaria Czech Republic

Romania Serbia0

20

40

60

80

100

68

4958 55

59

28

37 40

Majority group Roma

% Working age population participating in labor force

Facts do not accord with common perceptions: vast majority of Roma do not depend on social assistance

Bulgaria Romania Serbia0

20

40

60

80

100

1612

25

Proportion of population (%)

% Households receiving social assistance

Education facts accord with perceptions: the vast majority of Roma do not have a secondary education or higher

Bulgaria Czech Republic Romania Serbia0

20

40

60

80

100

8780

75 77

1320

12 13

Majority Group Roma

% Working age population with secondary and/or vocational

Roma Inclusion Requires a Multi-Dimensional Approach

Priority areas include:• Employment activation policies

• Ensuring equal education opportunities

• Addressing housing inequities

• Closing health disparities

Roma Inclusion: An Economic Opportunity

Experiences of the World Bank regarding the territorial approach

Katarina Mathernova 16 May 2011

LAU 1: Bulgaria Poverty Incidence Map

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

Poverty Mapping Program

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

Estimating EU Poverty Indicators @ LAU levels: Main Challenge

Source: “EU legislation on the 2011 Population and Housing Censuses” (Eurostat 2011, ISSN 1977-0375)

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

Small Area Estimation: Combine Census and Survey Information

Common Household Background CharacteristicsEU-SILC or other detailed

survey

Common Household Background Characteristics

National Population Census

Background characteristics unique to EU-

SILC

Household Welfare Indicator(s) such as at-risk-of-poverty in

EU-SILC

Step 0

Step 1

Household Welfare Indicator(s) such as

at-risk-of-poverty not in census

Step 2

POVERTY MAP(S)

Case Study: Bulgaria Poverty Incidence Maps

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

Case Study: Bulgaria Poverty Incidence Maps 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

Concluding Remarks