1. Joost de Laat (Phd) Human Development Europe and Central Asia The World Bank EURoma Meeting Budapest, Hungary Structural Funds: Investing in Roma 11 November 2011

2. Step 1: Identify vulnerable (Roma) communities Step 2: Identify critical gaps in human development outcomes Step 3: Institutionalize evaluation to learn which type of interventions are likely to have the highest impacts on specific outcomes Step 4: Ensure that inclusion programs clearly define the specific outcomes they hope to impact

4. What are poverty maps? Going from high level NUTS to small LAU areas Combining 2011 census information with EU- SILC survey information as a (potential) way to poverty mapping Bulgaria poverty mapping case study

6. http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/principles_characteristics

7. Example: Nuts 3 in Bulgaria represent 28 districts

8. http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/local_administrative_units

9. LAU 1 level (nuts 4) – 262 municipalities (2005)

10. 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

11. Common Household Background Characteristics EU-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)

12. Highly disaggregated databases of: Poverty Inequality Average income/consumption Calorie intake Under-nutrition Other indicators (health, employment etc) Disaggregation may, but need not, be spatial; e.g. poverty of statistically invisible groups

13. Goals Goals Identify poor municipalities targeting for poverty reduction Serve a basis for targeting for poverty reduction Implementation: Joint team Implementation: Joint team (Data Users Group) Leadership of the Ministry of Labor and Social Policy (MLSP) Technical expertise of the National Statistical Institute (NSI) Active involvement of leading Bulgarian academics World Bank financing and technical assistance trough a Capacity Building Institutional Development Fund (IDF) grant Outcomes Outcomes 2003 and 2005 poverty incidence maps

14. Methodology Methodology Data sources: 2001 Census and 2001 and 2003 Bulgaria Integrated Household Surveys (BIHS), and district level indicators BIHS: 2,500-3,023 households, representative at NUTS 1 (Sofia, urban, rural level) 30 common indicators between Census and BIHS Standard small-area estimation procedure Municipal level indicators estimated Municipal level indicators estimated Poverty rate, poverty depth, severity of poverty, and Gini coefficients

15. 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 Turkish households) Poorest areas characterized by lacking in: o human capital endowment (prevalence of people with low education attainment, or elderly pensioners), and o infrastructure

16. Policy use Policy use Strategic poverty documents, e.g. The National Plan for Poverty Reduction 2005-2006 Strategy for Reduction of Poverty and Social Exclusion 2006-08 District Development Strategies 2005-2015 Targeting of antipoverty interventions Program for Poverty Reduction in the (13) Poorest Municipalities Targeting of Social Investment Fund (SIF) projects included in a multi-dimensional continuous scoring formula applied for ranking of municipal proposals, along with other indicators Social Investment and Employment Promotion Project (WB)

17. Appropriate for targeting Poverty maps can be very useful tool to target poorest areas Implemented around the world. Window of opportunity: 2011 Censuses and annual EU-SILC survey data Involve community of Roma stakeholders to identify Roma communities on poverty map and build ownership

18. Reports Forthcoming 2011

19. Step 1: Identify vulnerable (Roma) communities Step 2: Identify critical gaps in human development outcomes Step 3: Institutionalize evaluation to learn which type of interventions are likely to have the highest impacts on specific outcomes Step 4: Ensure that inclusion programs clearly define the specific outcomes they hope to impact

20. Carry out qualitative case study work Analyze household survey data on vulnerable Roma communities and national surveys Implement pilot projects that include a rigorous counterfactual impact evaluation.

21. 21 Survey Partnership: DG Regional Policy United Nations Development Program World Bank Close coordination with survey by: Fundament Rights Agency

22. Report Forthcoming 2011

23. International evidence: high return investment Survey: vast majority Roma parents desire at least secondary education completion for children Report objectives: Provide overview of Roma preschool participation, and pre- school environment, in kindergartens and at home Identify key barriers to improving pre-school access 23

24. Enrollment among Roma children: very large gap 24 OVERVIEW OF PRE-SCHOOL ENVIRONMENT

25. Enrollment low, only slowly improving over time (except Hungary) 25 OVERVIEW OF PRE-SCHOOL ENVIRONMENT

26. Most parents with children in preschool feel they are welcome Most parents with children in preschool are satisfied with the preschool services 26

27. 27 Boost in: -Cognitive learning outcomes (except Romania) - parenting techniques also! -Avoiding special school in CZ, SL (table below) -Secondary school completion -Avoiding social assistance Bulgaria (N=1,441) Czech Republic (N=1,461) Hungary (N=1,887) Romania (N=1,785) Slovakia (N=1,195) (1)(3)(4)(6)(10)(12)(13)(15)(7)(9) Attended preschool as a child? 0.00432 (0.00440) 0.00207 (0.00514) - 0.0676*** (0.0244) -0.0568** (0.0246) 0.000262 (0.0138) -0.0135 (0.0163) 0.0168* (0.00904) 0.0145 (0.00960) -0.0489* (0.0281) -0.0735** (0.0307) Background households and individual level characteristics NoYesNoYesNoYesNoYesNoYes R2R2 0.1580.1730.3080.3350.2810.2870.1320.1480.2950.324

28. 28 Comparing neighbors with similar socio-economic chars, pre-school increases with: Parents attendance of pre-school Household hunger Roma – non-Roma gap (between neighbors) largely explained by socio-economic background

29. 29

30. 30

31. Many Roma parents would consider pre- school at lower costs Some parents of un-enrolled Roma children would reconsider with a Roma teacher / mediator in place 31 RESOLVING BARRIERS

32. 1. Informing Roma parents on the returns to pre- school (Community) health workers could play this role 2. Lowering the costs (e.g. fees, clothes, food) Providing information about government schemes that parents may be entitled to Providing material needs 3. Creating a bridge: community mediators supporting Roma parents access pres-school for their children 32

33. Carry out qualitative case study work Analyze household survey data on vulnerable Roma communities and national surveys Identifies gaps in human development outcomes Points to specific policies Can be used for other policy questions Can be institutionalized: e.g. Statistical Offices carry out EU-SILC booster samples in vulnerable communities Implement pilot projects that include a rigorous counterfactual impact evaluation.