An operational method for assessing the poverty outreach of development projects

( illustrated with case studies of microfinance institutions in developing countries)

Manohar Sharma

IFPRI

Overview

• Objectives for the development of the method

• Reasons for choice of method• Research approach in developing the

method• How is the index of relative poverty

computed?• Examples of results (India, Nicaragua,

South Africa)• Application potentials of the method

Outreach/Targeting to poor groups

Welfare impact

Financial sustainability of the institution

The critical triangle of institutional development

Source: Zeller, Manfred and Meyer, Richard L. 2000. The critical triangle of micro-finance.Upublished manuscript, IFPRI/Ohio State University.

Objectives of the research project

• It is not an impact evaluation tool • It is not a targeting tool• Develop an operational method that can

be used by donors to assess the poverty level of clients of mfis

• CGAP wanted that the method is: Easy to implement in a relatively short time Not costly Results should be comparable between

different mfis and, if possible, across countries

Principal methods

1. Typical living standard (expenditure) surveys too expensive and complicated

2. Participatory assessment methods not comparable, even between villages

3. Identification of a set of indicators which are used to build an index that is a measure of poverty:

Examples of indices already used: Housing index (for MFI-targeting in South and

Southeast Asia), but poverty has many dimensions (food, asset, social capital)

UN Human Development Index (3 components: income, education, and life expectancy)

But here arbitrary weights need method that objectively sets weights subject to country-specific conditions

Indicator Method - Multi-dimensions of Poverty

How many days in past month not enough to

eat?

Material of walls?

Number of rooms?

Food security Housing condition Assets

Human capital Other

Ownership of bicycle, TV etc

%of adults in household, that can read and

write

Relatives working in

foreign countries?

Poverty

Criteria for selection of indicators

• Nationally valid (can be used in different local contexts, urban vs. Rural)

• Not too sensitive question, can be asked Openly • Practicability (can be observed vs. Require interview)• Ability to discriminate different levels of poverty• Reliability (risks of falsification/error vs. possibility to

verify)• Simplicity (direct answer vs. computed information)• Time (Answer can be elicited quickly)• Universality (can be used in different countries)

Human resources Dwelling

Food security and vulnerability Assets Others

   Age and sex of adult household members   Level of education of adult household members   Occupation of adult household members   Number of children below 15 years of age in household   Annual clothing/ footwear expenditure for all household members

   Number of rooms   Type of roofing   Type of exterior walls   Type of flooring   Observed structural condition of dwelling   Type of electric connection   Type of cooking fuel used   Source of drinking water   Type of latrine

   Number of meals served in last two days   Serving frequency (weekly) of three luxury foods    Serving frequency (weekly) of one inferior food    Hunger episodes in last one month   Hunger episodes in last 12 months   Frequency of purchase of staple goods   Size of stock of local staple in dwelling

   Area and value of land owned   Number and value of selected livestock resources   Value of transportation-related assets   Value of electric appliances

   Nonclient’s assessment of poverty outreach of MFI

The comparison groups

• Compare level of poverty (or wealth) of RANDOMLY SELECTED new clients

With• Level of poverty (or wealth) of RANDOMLY

SELECTED non-clients in the operational area of the MFI

Principal component analysis

Poverty

Human resources

Dwelling Asset Food Other

Components

Indicators

Computing a poverty index

• Starting with a generic questionnaire, finalize situation specific indicators, questionnaire,

• Collect data on indicators• Construct household-specific poverty indices

as scores from Principal component analysis• • Separate out non-client households, sort, and

form three groups. Group 1= poorest, Group 2= poor, Group 3= less poor.

• Use score range for each group to classify client households.

To which of three poverty tercile groups do client households belong?

Poverty Index Score

Middle 100 non-client households

Bottom 100 non-client households

Top 100 non-client households

Cut-off score

-2.51 -0.70 0.21 3.75

Poorest Poor Less Poor

Poverty Score Index

Client Households

Comparing extent of poverty outreach

across programs and countries.

Measure 1: (percentage of clients belonging to poorest tercile) Higher values show more extensive outreach to the poorest

Measure 2: (percentage of clients belonging to Least poor tercile)Higher values show more outreach to the better-off

Measure 3: indicates whether poorer regions in the countryhave been reached

Case study in India with SHARE

• Provides credit and savings services to targeted poor individuals, mainly rural women in seven districts of Andhra Pradesh in India.

• Women self-selected, then tested for eligibility through questionnaire and interview.

• Has offered services to about 16,000 women with loan sizes in the range of $103 to $308 (year 2000).

• Loans provided without collateral to client groups of five, but require group training and certification.

Results for SHARE in India

58% of SHARE clients in “poorest” tercile, compared to 33% of non-clients

38.5% of SHARE clients in “poor” tercile compared to 33% on non-clients

3.5% of SHARE clients in “less poor” tercile, compared to 33% of non-clients

Poverty group

less poorpoorpoorestP

erc

en

t

70

60

50

40

30

20

10

0

client status

SHARE client

Non-client

Case study in Nicaragua with ACODEP

• ACODEP is the largest micro-finance institution in Nicaragua, serving 12,000 clients.

• Offers range of loan products to individuals for enterprise development ($20 to several thousand loan size).

• Offers savings programs specifically designed for poorer clients.

RESULTS FOR ACODEP IN NICARAGUA

30.9 % of ACODEP clients in “poorest” tercile, compared to 33% of non-clients

37.7 % of ACODEP clients in “poor” tercile compared to 33% on non-clients

31.4% of ACODEP clients in least poor tercile, compared to 33% of non-clients

Poverty group

Less poorPoorPoorest

Proz

ent

40

30

20

10

0

client-non client

non-client

client

Source: Lapenu, Zeller Nicaragua case study

South Africa: Comparison of two credit programs-- Small Enterprise Foundation (SEF)

NON- TARGETED

% client- household

s

% non-client

households Poorest 15 33

Poor 35

33

Less Poor 50 33

TARGETED % client

houshholds % non-client

households Poorest 52 33

Poor 39

33

Less Poor 9 33

Source: Carla Henry, Follow-up case study in South Africa