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