DEC Course on Poverty and Inequality Analysis Module 4: Poverty

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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

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

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

Non-Roma

Romania

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

Republic

Male LFP

Roma

Serbia

58

37

55

40

0

Bulgaria Czech

Republic

Romania

Roma

Serbia

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

Majority Group

Romania

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

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