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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
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
Poverty Monitoring/ M&E
Imple
menta
tion
Using MM&E to enhance development outcomes
Results
Poverty Diagnostics
Impact Evaluation
Ex-ante Impact Modeling(PSIA)
Strategies, allocation and
design
MM&E tools
Objectives: National process:
Better diagnostics on binding constraints to
poverty alleviation and equity.
Better ex-ante understanding of the
distributional impacts of reforms, better design.
Better ability to track progress and feedback into policy making.
Better understanding of which interventions reduce poverty; Building evidence-based policy.
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
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.
0
10
20
30
40
50
60
70
1980 1985 1990 1995 2000 2005
$2 per day
$2 per day (less China)
$1.25 per day
$1.25 per day (less China)
Headcount index (% below poverty line)
• 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
Measuring income poverty:
Progress uneven across regions
South Asia
Sub-Saharan Africa
East Asia and Pacific
Rest of the Developing World
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1981 1984 1987 1990 1993 1996 1999 2002 2005
Popu
latio
n liv
ing
unde
r $1.
25 p
er d
ay
(mill
ions
)
Revised Poverty Estimates
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
Non-Income Measures:
Malnourished Children (%)
Source: Online Atlas of the MDGs (World Bank)
Non-Income Measures:
Malnourished Children (number)
Source: Online Atlas of the MDGs (World Bank)
Resized based on number of children under 5 who are malnourished
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
Non-Income Measures:
Primary Completion (%)
Source: Online Atlas of the MDGs (World Bank)
Non-Income Measures:
Gender Equality in Education
Source: Online Atlas of the MDGs (World Bank)
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 by indicators, and is better grasped through use of qualitative/mixed methods.
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
Measuring women’s empowerment in Bangladesh
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.
Areas of New Analysis: Human Opportunity Index
Measuring Equality of Opportunity – within countries
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
Areas of New Analysis: Poverty Maps
Figure 2: Poverty Map at DS division level
Each dot is randomlyplaced within a DS unitand represents500 poor persons
Poverty Headcount Accessibility Index Distribution of the Poor
Poverty maps can improve policy design: Understanding spatial pattern of poverty and correlates Targeting programs and funding Monitoring progress and communicating results
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
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
THANK YOU