1. Boryana Gotcheva, Peter Lanjouw, Katarina Mathernova, and Joost de Laat The World Bank “How to Implement Strategies for Roma Integration with EU Funds” 21 June 2011, Sofia

2.  The rationale for poverty maps in the context of Roma integration and use of EU funds  The emergence of poverty mapping  The poverty mapping experience in Bulgaria  The way forward: combining 2011 census information with EU-SILC survey information as a (potential) way to poverty mapping  Concluding remarks

3. Poverty incidence in Bulgaria, LAU 1 level (‘nuts 4’) – 262 municipalities (2005)

4.  Not necessarily “maps”; rather, highly disaggregated databases highly disaggregated databases of welfare indicators ◦ Poverty and/or inequality ◦ Average income/consumption ◦ Calorie intake, under-nutrition ◦ Other indicators (health outcomes, life-expectancy, education attainment) targeting disaggregation may, but need not, be spatial  Can be used for targeting, moreover disaggregation may, but need not, be spatial “statistically invisible” ◦ Poverty of “statistically invisible” groups

5. targeting of social inclusion interventions  Poverty maps are an effective instrument for targeting of social inclusion interventions that go beyond cash social assistance means test enabling  The cash social assistance beneficiaries are identified with a means test, however they usually experience multiple vulnerabilities, that can be reduced by combining cash transfers with enabling Social care service Employment services / active labor market programs Housing projects Regional development initiatives, etc.  Poverty maps allow geographic cross-check on enrollment to validate patterns in eligibility decisions

6.  Program started late 1990s by the World Bank research department  “Small area estimation” methodology: a combination of highly disaggregated household-level micro data collected with HBS or LSMS, and all-encompassing census data  Methodological papers ◦ Elbers, Lanjouw and Lanjouw (2003, Econometrica) ◦ Hentschel et al. (2000) and ELL (2000, 2002)  Strong capacity building effort: poverty maps are now produced on a regular basis in all parts of the world  World Bank PovMap Software publicly available for small area estimation

7.  Goals ◦ Display spatial dimension of poverty and identify pockets of poverty targeting of disadvantaged municipalities ◦ Serve a basis for targeting of disadvantaged municipalities for the purposes of 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 ◦ 2003 and 2005 poverty incidence maps ◦ Book ◦ Featured in “More than a Pretty Picture” book and conference

8.  Methodology ◦ Data sources: 2001 Census and 2001 and 2003 Bulgaria Integrated Household Surveys (BIHS), 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

9. 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

10.  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)

11.  Combination of 2011 census and latest EU-SILC data  Household surveys like EU-SILC have breadth of indicators, but sample sizes too small to be representative for local area units do  Population census do allow small areas calculations but frequently lack breadth of indicators necessary to calculate main poverty indicators

12. 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)

13.  Appropriate for targeting  Appropriate for targeting. Poverty maps can be very useful tool to target poorest areas with inclusion programs  Implementation history and available capacity  Implementation history and available capacity. If data are available, production of poverty maps takes several months  Policy relevance  Policy relevance and adoption of poverty maps are enhanced through considerable outreach and capacity building  A window of opportunity in Bulgaria and EU- wide  A window of opportunity in Bulgaria and EU- wide: population censuses being implemented throughout the EU in 2011 and availability of annual EU-SILC survey data are promising

14. bgotcheva@worldbank.org