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Challenges of Measuring Poverty Reduction and Equality: Using statistics to assess results

Challenges of Measuring Poverty Reduction and Equality: Using statistics to assess results. Ana Revenga Director, Poverty Reduction Group World Bank Stockholm November 20, 2008. Overview. MM&E systems and the results agenda Measuring poverty

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Challenges of Measuring Poverty Reduction and Equality: Using statistics to assess results

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  1. Challenges of Measuring Poverty Reduction and Equality: Using statistics to assess results Ana Revenga Director, Poverty Reduction Group World Bank Stockholm November 20, 2008

  2. Overview • MM&E systems and the results agenda • Measuring poverty • Income/Consumption poverty: new global estimates • Non-income poverty: MDGs, voice and empowerment • Areas of new analysis • Measuring equality of opportunities • Measuring service delivery • Poverty maps • Country level monitoring systems • Tracking program effectiveness & poverty impacts • Integrating M&E into government processes

  3. Using MM&E to enhance development outcomes Objectives: National process: MM&E tools Better diagnostics on binding constraints to poverty alleviation and equity. Strategies, allocation and design Poverty Diagnostics Better ex-ante understanding of the distributional impacts of reforms, better design. Ex-ante Impact Modeling (PSIA) Better ability to track progress and feedback into policy making. Poverty Monitoring/ M&E Implementation Better understanding of which interventions reduce poverty; Building evidence-based policy. Impact Evaluation Results

  4. Challenges of Measuring Global (Income) Poverty • How do we talk meaningfully about “global poverty”? • Poverty lines across countries vary in terms of their purchasing power • To measure global poverty, we need to apply a common standard, anchored to what “poverty” means in the world’s poorest countries • International comparisons of poverty require PPP, but previous estimates (1993 PPPs) biased • Cost of living underestimated in poor countries; quality and price differences confused • Other weaknesses: country coverage (no China), urban bias • 2005 International Comparison Program (ICP) improves PPP and poverty estimates • Coverage increased to 146 economies (many more Africa + China) • Revised international poverty line = $1.25 / day • Global headcount poverty revised upward (1.4 billion), but trend in poverty reduction still robust

  5. Measuring income poverty:New global estimates higher, but poverty falling The % below $1.25 a day was halved, falling from 52% to 26% over 1981-2005. Trend decline of one % point per year. At this rate, the developing world as a whole is on track for attaining the first MDG. • Number of poor fell by 500 million, from 1.9 billion to 1.4 billion • Poverty rate fell in all years • Robust to choice of poverty line

  6. Measuring income poverty:Progress uneven across regions Revised Poverty Estimates

  7. Challenges of Measuring Non-Income Dimensions of Poverty • More difficult than using more traditional income/consumption based metrics • “Non-monetary” indicators • may change more slowly than monetary indicators • can be more difficult (and costly) to collect • may require special surveys • more context-specific and less “universal” • may be less tangible and quantifiable • …hence perceived as less objective and rigorous

  8. Non-Income Measures:Malnourished Children (%) Source: Online Atlas of the MDGs (World Bank)

  9. Non-Income Measures:Malnourished Children (number) Resized based on number of children under 5 who are malnourished Source: Online Atlas of the MDGs (World Bank)

  10. Non-Income Measures:Access to Education • Africa: Enrollment rates have risen, but male-female gap has not significantly narrowed. • SA and MENA: Male-female enrollment gap narrowed. Progress in enrollments for ‘last’ 10-20% is slow. • EAP: Net enrollment rates for male and female children decreased slightly • LAC & ECA: Fairly stable

  11. Non-Income Measures:Primary Completion (%) Source: Online Atlas of the MDGs (World Bank)

  12. Non-Income Measures:Gender Equality in Education Source: Online Atlas of the MDGs (World Bank)

  13. Non-Income Measures:Measuring Empowerment • Empowerment: expansion of capabilities of poor to participate in, negotiate with and influence institutions that affect their lives • Institutional Climate • Social and political structures • Individual assets and capabilities • Collective assets and capabilities • Empowerment is difficult to measure quantitatively and benefits from a mixed method approach: • Access to most assets can be measured by indicators (but qualitative methods better at evaluating psychological, social assets) • Institutional context can be only partially measured byindicators, and is better grasped through use of qualitative/mixed methods.

  14. Measuring women’s empowerment in Bangladesh Empowerment indicators (results further explored through focus groups) included: • Control over assets (husband, self, joint, others) • Participation in village meetings and elections (& if not, why not) • Participation in household decision making (husband, self, joint, others) about expenditures, children, joining organizations • Autonomy (visiting & purchases) • Domestic violence

  15. Areas of New Analysis:Measuring Inequality of Opportunities • The Human Opportunity Index (HOI) measures differences in opportunity among children. • The HOI synthesizes both the absolute level of basic opportunities in a society and how equitably those opportunities are distributed. • As the answers are aggregated across services, children and circumstances, a picture arises of how equitable (or not) a society is.

  16. Areas of New Analysis:Human Opportunity Index

  17. Measuring Equality of Opportunity – within countries

  18. Areas of New Analysis:Measuring Service Delivery • Service delivery information may be used to increase accountability • Administrative data, facility surveys, PETs • Data may be used to deepen our understanding of poverty and inequality and target policy responses • Linking LSMS and facility surveys • Careful evaluation aimed at answering key questions of design and the resulting effects can be used to increase the effectiveness of existing programs

  19. Each dot is randomly placed within a DS unit and represents 500 poor persons Areas of New Analysis:Poverty Maps • Poverty maps can improve policy design: • Understanding spatial pattern of poverty and correlates • Targeting programs and funding • Monitoring progress and communicating results Poverty Headcount Accessibility Index Distribution of the Poor

  20. Country level statistical and monitoring systems • Country’s statistical capacity is critical • Not only for tracking indicators • But for supporting rational decision making, policy design and implementation • But for results, must link M&E to strategy and budget • To have an impact, monitoring and evaluation data must be used for policy formulation and budgeting • Requires strong political leadership, coordination, and dissemination of results • Basics first • Focus on strengthening and harmonizing existing processes • Don’t rely on technical fixes alone • Create demand among policy makers and stakeholders

  21. Country level M&E Systems: Lessons from Uganda • M&E results can have big impacts • Public Expenditure Tracking Survey (PETS) used in 1996 to identify leakage in funding flow to primary school • Found only 13% of funds reached schools in 1991-95 • Greater transparency increase flow to 80-90% in 1999-2000 • Build on existing systems • National Integrated M&E System (NIMES) created to coordinate and harmonize 16+ existing systems • Intended to relieve data-collection burden and reduce multiplicity of performance indicators • Link strategy and budget processes • Poverty Action Fund (PAF) links Poverty Reduction Strategy priorities to budget

  22. THANK YOU

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