Targeting through Social Norms: Experimental Evidence from India's #GiveItUp Campaign
Last registered on May 22, 2019

Pre-Trial

Trial Information
General Information
Title
Targeting through Social Norms: Experimental Evidence from India's #GiveItUp Campaign
RCT ID
AEARCTR-0001048
Initial registration date
December 13, 2018
Last updated
May 22, 2019 2:01 PM EDT
Location(s)

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Primary Investigator
Affiliation
Michigan State University
Other Primary Investigator(s)
PI Affiliation
Yale University
Additional Trial Information
Status
On going
Start date
2016-04-01
End date
2019-12-31
Secondary IDs
Abstract
Social norms about who is deserving may help target public benefits, by making sure people in need receive benefits or by excluding people with lesser need to reduce program costs. The Government of India launched a campaign to use norms to improve the targeting of a cooking gas subsidy used by 220 million beneficiary households. The campaign, called Give It Up, asks beneficiary households to voluntarily forfeit cooking gas subsidies so the money can be used to subsidize the poor instead. We propose a field experiment to test the efficacy of self-targeting as a policy instrument and to measure whether the campaign induces spillovers in giving across households. The main policy outcome, usage of the cooking gas subsidy, is measured with high-quality administrative data in a sample of 1.2 million gas-using households. The cluster-randomized design will provide the first experimental estimates of the strength of spillover effects in charitable giving.
External Link(s)
Registration Citation
Citation
Barnwal, Prabhat and Nicholas Ryan. 2019. "Targeting through Social Norms: Experimental Evidence from India's #GiveItUp Campaign." AEA RCT Registry. May 22. https://www.socialscienceregistry.org/trials/1048/history/46972
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Experimental Details
Interventions
Intervention(s)
Treated households are sent a mail package which consists of a letter requesting them to enroll in an ongoing charitable giving campaign to donate their fuel subsidy. Each mail package also includes an enrollment form and provides details on how to enroll online or via text message. Additionally, a sticker is included in the mail to a sub-sample of recipients, which can be used by the recipient to indicate that the recipient has enrolled. We further conduct an in-person charitable solicitation with a sub-sample of households.
Intervention Start Date
2018-09-24
Intervention End Date
2019-02-15
Primary Outcomes
Primary Outcomes (end points)
[1] (a) Whether a household has donated the subsidy, (b) Household's future usage of the subsidized fuel.
[2] The magnitude of the spillover effect.
[3] In-person survey will provide a set of outcomes on-- concerns for fairness and redistribution, donations to other charitable causes, motivations for charitable donation, attitude about government welfare programs, knowledge about the monetary value of the fuel subsidy, knowledge about the charitable campaign, and channels through which the respondent learns about the charitable campaign.
[4] Household's donation in response to an in-person solicitation for charity.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We use a randomization design which includes cluster-level assignment of treatment saturation and individual-level assignment of treatment. Out of 1.2 million urban households in 3,802 clusters, 100,000 households are treated in a direct-marketing intervention. In the relative saturation design used in this study, each cluster is randomly allocated to one of the five bins (0%, 25%, 50%, 75% and 100%) of saturation, that means in a cluster allocated to 25% bin, only 25% randomly selected households are solicited for charitable donation via direct-marketing.
Within a cluster, households are randomly assigned to treatment groups. The content of the letter is determined using a cross-randomized design where specific messages are provided individually or jointly. On the top of the “basic appeal” content, we add four type of messages- Social distance, Information on the monetary value of subsidy, Signaling, Moral suasion. We further create two variations each under “Information on the monetary value of subsidy” and “Signaling”. This provides us total 36 groups, where a treated household is randomly assigned to. Finally, within the “Social distance” message, we randomly vary the examples on lines of caste-religion similarity.
Experimental Design Details
Not available
Randomization Method
Randomization is done in office using the statistical software package STATA
Randomization Unit
First, clusters are randomized for treatment saturation using a relative saturation design. Next, the treatment assignment and content type is randomly assigned to households in each cluster.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
Total 3,802 Clusters. These clusters are identified as a group of households who live in the same neighborhood. We have two type of clusters in this study- societies (449) and areas (3,353). "Societies" are sampled using a combination of rigorous data cleaning and field work. "Areas" are sampled using the classification available in the administrative data.
Sample size: planned number of observations
1.2 million households. 100,000 households receive treatment. We expect to survey about 7,500 households from this sample after direct-marketing solicitation. We will also survey about 500 additional households who had donated their cooking gas subsidy before our intervention.
Sample size (or number of clusters) by treatment arms
Number of clusters by treatment-fraction arms are as follows:
0% saturation bin - 3128 clusters (193 societies , 2,935 areas)
25% saturation bin- 169 clusters (64 societies, 105 areas)
50% saturation bin-169 clusters (64 societies, 105 areas)
75% saturation bin- 168 clusters (64 societies, 104 areas)
100% saturation bin- 168 clusters (64 societies, 104 areas)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Institute for Financial Management & Research Institutional Review Board
IRB Approval Date
2017-10-23
IRB Approval Number
NA
IRB Name
Yale University Institutional Review Board
IRB Approval Date
2016-03-23
IRB Approval Number
1602017217
IRB Name
Michigan State University Institutional Review Board
IRB Approval Date
2016-02-20
IRB Approval Number
i050749