Effective Targeting of Anti-Poverty Programs in Indonesia

Last registered on November 20, 2013


Trial Information

General Information

Effective Targeting of Anti-Poverty Programs in Indonesia
Initial registration date
Not yet registered
Last updated
November 20, 2013, 3:53 PM EST


Primary Investigator

Harvard University

Other Primary Investigator(s)

PI Affiliation
Stanford University
PI Affiliation
World Bank
PI Affiliation
PI Affiliation

Additional Trial Information

Start date
End date
Secondary IDs
In developing countries, identifying the poor for the purposes of redistribution or social insurance programs is challenging because the government lacks reliable information about people’s incomes. In Indonesia, the Government had relied primarily upon two basic types of methods to define the poor: proxy-means testing (PMT) method and community targeting methods. The objective of this study in the near term was to help the Government of Indonesia (Statistics Indonesia – BPS in particular) in formulating better indicators to improve identifying poor households eligible for a variety of assistance programs. And in the long term, the research findings will help to inform the Government about which targeting approaches are most efficient and cost-effective, including a direct comparison of the PMT method versus community targeting methods. This research was a collaborative effort between the Indonesia’s Ministry of Planning (BAPPENAS), Central Bureau of Statistics (BPS), World Bank Office Jakarta (WBOJ) and Jameel Poverty Action Lab (J-PAL).
External Link(s)

Registration Citation

, et al. 2013. "Effective Targeting of Anti-Poverty Programs in Indonesia." AEA RCT Registry. November 20. https://doi.org/10.1257/rct.97-1.0
Sponsors & Partners

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Experimental Details


We randomly assigned sub-villages to different method of targeting: Proxy Mean Testing (PMT), Community and Hybrid (combination of PMT and community). In the PMT treatment, targeting of households was based on predicting household’s consumption through data on household characteristics. In the community treatment, the residents of the neighborhood determine the list of beneficiaries through a facilitated, participatory poverty ranking exercise held at a community meeting. And the hybrid method combines the community ranking procedure with a subsequent PMT verification before households can be fully eligible.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Targeting performance and Satisfaction
Primary Outcomes (explanation)
Targeting performance: Household expenditure, community ranking; Satisfaction: fund disbursement, satisfaction, appropriateness, number of households that that should be added to the list, number of households should be subtracted from the list.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Within 3 provinces (North Sumatera, South Sulawesi and Central Java), 640 villages are selected randomly, stratifying the sample to consist of approximately 30% urban and 70% rural. For each village, we randomly selected one sub-village for the experiment. In each sub-village, an unconditional cash transfer was implemented. Each beneficiary household would receive a one time, $3 transfer. Each sub-village was randomly allocated to one of the three targeting methods (Proxy Mean Testing, Community or Hybrid). The number of households that would receive the transfer was set in advance through a geographical targeting approach, such that the fraction of households in a sub-village that would receive the subsidy was held constant, on average, across the treatment. After the beneficiaries were finalized, the funds were distributed. To publicize the lists, the program staff posted 2 copies of it in the visible locations. They also placed a suggestion box and a stack of complain cards next to the list.
Experimental Design Details
Randomization Method
Computer random number generator
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
640 villages
Sample size: planned number of observations
5,756 households
Sample size (or number of clusters) by treatment arms
209 villages got PMT method, 214 villages got community method and 217 villages got hybrid method.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
February 28, 2009, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
March 14, 2009, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
640 villages
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
5,756 households
Final Sample Size (or Number of Clusters) by Treatment Arms
209 sub villages got PMT method, 214 villages got community method and 217 villages got hybrid method
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials