Testing Targeting Variants for Emergency Transfers in DRC

Last registered on July 20, 2023


Trial Information

General Information

Testing Targeting Variants for Emergency Transfers in DRC
Initial registration date
July 20, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
July 20, 2023, 5:58 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.


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Primary Investigator

World Food Programme

Other Primary Investigator(s)

PI Affiliation
World Bank
PI Affiliation
PI Affiliation
Università degli Studi di Milano-Bicocca
PI Affiliation
World Bank
PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Governments and international organizations around the globe implement specific targeting approaches to identify the beneficiaries of their programs. The choice of a specific targeting approach and its consequences on individuals and communities have been highly debated. In this study, realized in collaboration with the World Food Programme (WFP), we compare the relative effectiveness of two targeting approaches that aim to identify the households most in need of food aid in a fragile setting. The first approach is data-driven and represents the current status quo. The identification of beneficiaries rests on a standard proxy mean testing (PMT) approach, augmented with inputs from focus groups conducted across 3 communities that could highlight criteria that are particularly relevant to the study context (any criteria emerging from the focus group would then be applied across all target communities). The second, new, approach is instead fully community driven: a local community committee is set up within each target community and is exclusively in charge of identifying all and only criteria to be used to select beneficiaries within that community. The study is based on a cluster randomized trial (experimental) approach: 84 community “blocs” in DRC’s Tanganyika Province were randomly assigned to one of the two targeting variants. We will collect data from a representative sample of 40 households in each community to assess how the two approaches differ in terms of targeting (inclusion/exclusion errors), community satisfaction, social cohesion, and women empowerment.

More specifically, the primary research questions are the following:
a. How does the status-quo data-driven “proxy mean testing plus” (PMT+) targeting approach compare in terms of targeting precision (inclusion/exclusion error), with respect to a committee-based (CB) approach?
b. How does the status-quo data-driven “proxy mean testing plus” (PMT+) targeting approach compare in terms of social cohesion, community satisfaction, and women’s agency, with respect to a committee-based (CB) approach?
c. Does the overall effectiveness of an aid program in a fragile setting differ based on the targeting approach used?
d. Which targeting approach is faster or more cost-effective?
External Link(s)

Registration Citation

Dunsch, Felipe Alexander et al. 2023. "Testing Targeting Variants for Emergency Transfers in DRC." AEA RCT Registry. July 20. https://doi.org/10.1257/rct.10350-1.0
Sponsors & Partners

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Experimental Details


The two experimental groups are:
• Data-driven (PMT+) approach: This is the current status quo approach, which heavily relies on data. Targeting is based on two inputs: a proxy means testing (PMT) formula that uses data collected from a community census, which is complemented with inputs collected through focus groups conducted in three communities. The focus groups are conducted separately with men and women, and have the objective to highlight dimensions that are considered by the group as a priority for identifying deserving beneficiaries in the local context. The criteria identified by the focus groups are then applied across all target communities. The final targeting thus combines the results from the PMT with the additional inclusion criteria identified by the focus groups. The approach is known as Proxy means testing 'plus' (PMT+). This status quo approach will serve as the benchmark (or “control”) group.
• Community-based (CB) approach: this is the new approach, which fully relies on community committees to identify the criteria for inclusion of assistance. A committee is set up in each target community and it is asked to list all inclusion criteria they consider relevant. Final targeting will be exclusively based on the criteria identified by the community.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Inclusion/exclusion errors
Satisfaction with the process

We also anticipate testing for heterogeneity of the impact based on:
Community size
Receipt of assistance (community coverage rates)
Primary Outcomes (explanation)
Inclusion and exclusion error will be computed on the basis of census data collected from all households in the community before the beginning of the intervention.

Secondary Outcomes

Secondary Outcomes (end points)
Social cohesion
Women’s empowerment
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study is a stratified cluster randomized controlled trial embedded in the expansion of WFP activities in the Tanganyika Province of DRC. 84 trial clusters, organized into 4 axes that span 3 'groupement' in the Tanganyika Province of DRC will participate in the trial. Each trial cluster corresponds to an administrative 'bloc', Within each of the 4 axes, the blocs will be grouped in quadruplets, according to bloc size (number of households) and groupement. Within each quadruplet, blocs will be randomly divided into a data-driven (PMT+) and a community-based (CB) group (randomized block design), using balanced randomization. In blocs assigned to PMT, beneficiaries are identified following the WFP status-quo data-driven approach, while in blocs assigned to CB, beneficiaries are identified based on the indications provided by the community, as explained above.
Experimental Design Details
Not available
Randomization Method
The randomizations will be implemented using a random number generator on a computer.
Randomization Unit
The unit of randomization will be the bloc (community). Each bloc in the sample hosts around 125 households.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
84 blocs
Sample size: planned number of observations
3360 households
Sample size (or number of clusters) by treatment arms
42 blocs PMT+ approach, 42 blocs community-based approach
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Milan-Bicocca Ethics committee
IRB Approval Date
IRB Approval Number