Joost de Laat (Phd) Human Development Europe and Central Asia The World Bank

1. Identify the Gaps, Measure Progress, and Promote Learning for a More Efficient Use of EU Structural Funds EURoma Meeting Budapest, Hungary Structural Funds: Investing in Roma 11 November 2011 Joost de Laat (Phd) Human Development Europe and Central Asia The World Bank

2. Promote Learning and Measure Progress 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

3. Step 1: Identifying vulnerable (Roma) communities

4. Outline • 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

5. Estimating EU Poverty Indicators @ LAU Levels

6. How to go from ‘high-level’ NUTS…? http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/principles_characteristics

7. Example: NUTS 3 Example: Nuts 3 in Bulgaria represent 28 districts

8. …down to ‘Local Administrative Units’ LAU levels 1 and 2? http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/local_administrative_units

9. LAU 1: Bulgaria Poverty Incidence Map LAU 1 level (‘nuts 4’) – 262 municipalities (2005)

10. Estimating EU Poverty Indicators @ LAU levels: Main Challenge In summary: • Household survey like EU-SILC have breadthof 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)

11. Small Area Estimation: CombineCensus and Survey Information Step 1 Background characteristics unique to EU-SILC Common Household Background Characteristics EU-SILC or other detailed survey Household Welfare Indicator(s) such as at-risk-of-poverty in EU-SILC Step 0 Step 2 Household Welfare Indicator(s) such as at-risk-of-poverty not in census Common Household Background Characteristics National Population Census POVERTY MAP(S)

12. What are Poverty Maps? • 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. Bulgaria Poverty Map Case Study • Goals • Identify poor municipalities • Serve a basis for targeting for poverty reduction • 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 • 2003 and 2005 poverty incidence maps

14. Bulgaria Poverty Map Case Study • 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 • Poverty rate, poverty depth, severity of poverty, and Gini coefficients

15. Bulgaria Poverty Map Case Study 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: • human capital endowment (prevalence of people with low education attainment, or elderly pensioners), and • infrastructure

16. Bulgaria Poverty Map Case Study • 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. Identify vulnerable communities concluding Remarks • 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. THE PILOT PROJECT ON ROMA INCLUSION: LESSONS BEING LEARNT FROM REGIONAL SURVEY Reports Forthcoming 2011

19. Promote Learning and Measure Progress 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. Identify gaps in outcomes and use monitoring and evaluation to learn which programs work best • 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. Roma Regional Household Survey (2011) • Survey Partnership: • DG Regional Policy • United Nations Development Program • World Bank • Close coordination with survey by: • Fundament Rights Agency

22. Policy question: Improving access to preschool Report Forthcoming 2011

23. IMPROVING ACCESS TO PRE-SCHOOL • 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

24. Overview of Pre-school environment • Enrollment among Roma children: very large gap

25. Overview of Pre-school environment • Enrollment low, only slowly improving over time (except Hungary)

26. Overview of Pre-school environment • Most parents with children in preschool feel they are welcome • Most parents with children in preschool are satisfied with the preschool services

27. HIGH RETURNS TO PRESCHOOL • Boost in: • Cognitive learning outcomes (except Romania) - parenting techniques also! • Avoiding special school in CZ, SL (table below) • Secondary school completion • Avoiding social assistance

28. ESTIMATING DETERMINANTS OF PRESCHOOL ENROLMENT 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. Determinants of pre-school enrolment

30. Determinants of pre-school enrolment

31. ReSOLVING BARRIERS • 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

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

33. Leveraging Monitoring and Evaluation: Conclusion • 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.