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Identifying most vulnerable (Roma) communities in Slovakia. Joost de Laat (Phd) Senior Economist Human Development Europe and Central Asia The World Bank. Outline. 2012 Slovakia Poverty Mapping project – Statistical Office/WB

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Identifying most vulnerable roma communities in slovakia

Identifying most vulnerable (Roma) communities in Slovakia

Joost de Laat (Phd)

Senior Economist

Human Development Europe and Central Asia

The World Bank


Outline
Outline

  • 2012 Slovakia Poverty Mapping project – Statistical Office/WB

  • 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



How to go from high level nuts
How to go from ‘high-level’ NUTS…?

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


Example nuts 3
Example: NUTS 3

Example: Nuts 3 in Slovakia represent 8 regions


Down to local administrative units lau levels 1 and 2
…down to ‘Local Administrative Units’ LAU levels 1 and 2?

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


Lau 1 bulgaria poverty incidence map
LAU 1: Bulgaria Poverty Incidence Map

LAU 1 level (‘nuts 4’) – 262 municipalities (2005)


Estimating eu poverty indicators @ lau levels main challenge
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)


Small area estimation combine census and survey information
Small Area Estimation: ChallengeCombineCensus 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)


What are poverty maps
What are Poverty Maps? Challenge

  • Highly disaggregated databases of:

    • Poverty

    • Inequality

    • Average income/consumption

    • Calorie intake

    • Under-nutrition

    • Other indicators (health, employment etc)


Bulgaria poverty map case study
Bulgaria Poverty Map Case Study Challenge

  • 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


Bulgaria poverty map case study1
Bulgaria Poverty Map Case Study Challenge

  • 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


Bulgaria poverty map case study2
Bulgaria Poverty Map Case Study Challenge

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


Bulgaria poverty map case study3
Bulgaria Poverty Map Case Study Challenge

  • 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)


Identify vulnerable communities concluding remarks
Identify vulnerable communities concluding Remarks Challenge

  • 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 – Slovak Roma Atlas