Targeting the Poor: Evidence

from a Field Experiment in

Indonesia

Alatas, Banerjee, Hanna, Olken and Tobias

American Economic Review 2012, 102(4):1206-

1240

Agenda

Background

The Direct Cash Assistance (BLT)

program was launched in 2005 to

support poor households during

economic crisis.

How to find an appropriate approach

to target the poor.

Reports an experiment on three

approaches: proxy means tests

(PMT), community targeting, and a

hybrid.

Proxy Means Test (PMT)

Assets (as proxy) are used to predict consumption or income

Frequently being used to the selection of the beneficiaries in a targeted social safety net programs.

Only those with incomes below a certain threshold are eligible.

The presumption is that household assets are harder to conceal from government surveyors than income.

Community-Based

The government allows the community

or some part of it to select the

beneficiaries.

The presumption is that wealth is

harder to hide from one’s neighbors

than from the government.

Hybrid

Combines PMT with community-based

method.

Aims to take advantage of the relative

benefits of both methods.

I. Empirical Design

Setting Indonesia

Cash transfers US$10 (BLT Programs)

Combination of PMT with community-based

methods

Goal: the poorest one-third of households.

45% of funds were incorrectly provided to non

poor households; 47% of the poor were

excluded from the program in 2005-2006

(World Bank:2006)

I. Empirical Design

Sample: 3 provinces640 villages30% urban70% rural

Experimental design Treatment for PMT Treatment for Community Targeting Treatment for Hybrid

North Sumatra

Central Java

South Sulawesi

II. Describing the Data

Data Collection

Four main sources of data:Baseline data

•demographics

•Family networks

•Participation in community activities

•Relationships with local leaders

•Access to existing social transfer programs

•Households’ pecapita consumption

Data on treatment results

•Targeting rank list

Data on community

meeting

•Attendance list

•Questionnaire on perceptions of community’s interest and satisfaction level

Data on community satisfaction

•Suggestion boxes

•Subvillage head interviews

•Facilitator feedback

•Households interview

II. Describing the DataSummary Statistics

32%: incorrectly

targeted based

on consumption

20% of non poor

households

received cash

transfer

53% of the poor

excluded

III. Comparing the Methods

Results on Targeting

Performance and Satisfactiono Targeting Performance Based on Per Capita

ConsumptionPMT method outperforms both the community and hybrid treatment in terms of the consumption based error rate.

o Effects of Targeting Policy on Poverty Rate and Gap- The differences in targeting accuracy across the

three methods do not result in large differences in the measures of poverty under consideration.

- Community treatments do better at reducing the poverty headcount (from 15.64 to 13.68)

- The poverty gap is not significantly different among he three methods.

o Satisfaction

Data collection: end line household

survey, follow up survey of sub village

heads, and comment box, community’s

complaints, facilitator comments.

Results:

Individuals and sub village heads are

much more satisfied with the community

treatment.

Fewer complaints in the community

treatments.

IV. Elite Capture

Examining whether elite connected

households are more likely to be

beneficiaries when the elite have more

control of the process

Result: the elite capture is not the

reason that the targeting is worse

under the community method.

V. Community Effort

• Worse targeting in the community methods could result simply from fatigue as a the ranking progresses.

• To investigate, they randomized the order in which households were ranked and did regression.

• Results: the community treatment does slightly better than the PMT in the beginning but substantially worse towards the end.

VI. Testing the Maximand

The community is doing its best to identify the poor, but has a different concept of poverty.

Investigated by examining how the targeting outcomes compare not just against the government’s metric of welfare, but also against alternative welfare metrics (community, sub village head, and self-assessment survey ranks)

Results:Per capita consumption does not fully capture what

the community calls welfare.

The community and the elite broadly share the assessments of welfare

The community targeting methods are more likely to conform with individual’s self-identified welfare status.

Does the community lack

information to evaluate

consumption?

Community has residual information

about consumption beyond that

contained in the PMT score or even in

the PMT variables. Community has

most of the information in the PMT as

well, but choose to aggregate it in

different way.

A different view of individual welfare

People believe that there are household economies of scale, so that conditional on per capita consumption.

The community may know more about other households’ ability to smooth shocks.

No evidence that ethnic minorities are more likely to be ranked as poor.

Those who contribute money are likely to be ranked as richer.

Communities may try to provide the “right” incentives to households.

Village does not penalize those who spend a lot of money on smoking and drinking

Conclusion

The community seems to have widely shared objective function other than per capita consumption;

The objective function does not differ based on elite capture;

There are better understanding of factors that affect a household’s earning potential or vulnerability.

If targeting the poor based on consumption is the only objective, the PMT performs better than community methods.

Community does better at identifying the poor.

Thank You for Listening