Poverty Maps to Improve Targeting and to Design Better Poverty Reduction and Social Inclusion Policies: the Case of Bulgaria

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

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

Outline

More than a pretty picture…

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

Not necessarily “maps”; rather,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)

Can be used for targeting, moreover disaggregation may, but need not, be spatial◦ Poverty of “statistically invisible” groups

Rationale for Poverty Maps

Poverty maps are an effective instrument for targeting of social inclusion interventions that go beyond cash social assistance

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

Rationale for Poverty Maps

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

Emergence of Poverty Mapping

Goals◦ Display spatial dimension of poverty and identify pockets of poverty◦ Serve a basis for targeting of disadvantaged municipalities for the

purposes of 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 ◦ Book◦ Featured in “More than a Pretty Picture” book and conference

The Case of Bulgaria: Poverty Incidence Maps (1)

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

The Case of Bulgaria:Poverty Incidence Maps (2)

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), ando infrastructure

The Case of Bulgaria: Poverty Incidence Maps (3)

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)

The Case of Bulgaria:Poverty Incidence Maps (4)

The Way Forward: New Poverty Incidence Maps

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

Population census do allow small areas calculations but frequently lack breadth of indicators necessary to calculate main poverty indicators

Small Area Estimation: Combine Census and EU-SILC 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)

Appropriate for targeting. Poverty maps can be very useful tool to target poorest areas with inclusion programs

Implementation history and available capacity. If data are available, production of poverty maps takes several months

Policy relevance and adoption of poverty maps are enhanced through considerable outreach and capacity building

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

Concluding Remarks

THANK YOU!

bgotcheva@worldbank.org