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Academic Ambassadors and the Diffusion of Digital Financial Services among the Peruvian Poor
Last registered on January 05, 2018

Pre-Trial

Trial Information
General Information
Title
Academic Ambassadors and the Diffusion of Digital Financial Services among the Peruvian Poor
RCT ID
AEARCTR-0002479
Initial registration date
January 03, 2018
Last updated
January 05, 2018 3:49 PM EST
Location(s)
Region
Primary Investigator
Affiliation
Universidad de Piura
Other Primary Investigator(s)
PI Affiliation
Universidad de Piura
PI Affiliation
Aix-Marseille Université
PI Affiliation
Virginia Tech
PI Affiliation
Universidad del Pacifico
PI Affiliation
Instituto de Estudios Peruanos
Additional Trial Information
Status
On going
Start date
2017-09-16
End date
2019-03-31
Secondary IDs
Abstract
We propose to study a BIM diffusion strategy in which academically successful individuals from targeted communities play the primary role in spreading information and training. These individuals are drawn from Beca18, a social inclusion program in higher education that facilitates access to post-secondary studies for impoverished high school graduates. In other words, we will explore whether adoption of financial technologies among the poor can be speeded-up by using role models from the community in the diffusion process.
To implement our RCT, first we will invite Beca18 fellows at a local private university in Peru, to be part of a campaign supporting the diffusion of financial services in their neighborhoods/communities, with no mention of the BIM or the specific role they might play in its diffusion. Half of the volunteers will be randomly selected to diffuse information and training related to the new BIM to their household network. In the case of the other half, their household network will receive information and training related to the new BIM by an external agent
For each Beca18 fellow in our intervention, we will map their household network within their neighborhood/community by asking them who the adult members in their household interact with in their neighborhood/community. They will also be asked to rank these household links in terms of the interaction intensity. We will select 10 to 12 members from this set and invite them to participate in the BIM training sessions.



External Link(s)
Registration Citation
Citation
Agurto, Marcos et al. 2018. "Academic Ambassadors and the Diffusion of Digital Financial Services among the Peruvian Poor." AEA RCT Registry. January 05. https://doi.org/10.1257/rct.2479-1.0.
Former Citation
Agurto, Marcos et al. 2018. "Academic Ambassadors and the Diffusion of Digital Financial Services among the Peruvian Poor." AEA RCT Registry. January 05. http://www.socialscienceregistry.org/trials/2479/history/24760.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
We propose to study an electronic wallet (the Peruvian BIM) diffusion strategy in which academically successful individuals from targeted communities play the primary role in spreading information and training. These individuals are drawn from Beca18, a social inclusion program in higher education that facilitates access to post-secondary studies for impoverished high school graduates. In other words, we will explore whether adoption of financial technologies among the poor can be speeded-up by using role models from the community in the diffusion process.
Intervention Start Date
2017-09-16
Intervention End Date
2018-12-31
Primary Outcomes
Primary Outcomes (end points)
The primary outcome variables of our study are the decisions to adopt and effectively use the new electronic wallet BIM.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
We will also study outcomes related to financial inclusion and poverty such as savings; access to formal financial services; capacity to smooth consumption shocks; intrahousehold decisions; assets accumulation; access to government benefits; etc. We also plan to test for heterogeneous effects: whether male or female Beca18 ambassadors have a higher influence in the diffusion process, or explore which type of individuals are more likely to be affected by Beca18 ambassadors.
Finally, we will also aim to explore whether individuals in the treated group are more likely to pass on the information they receive to others in their own network, and how this affects BIM adoption by the others. In this case we will work with self-reported data.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
To implement our RCT, first we will invite Beca18 fellows at a local private university in Peru, to be part of a campaign supporting the diffusion of financial services in their neighborhoods/communities, with no mention of the BIM or the specific role they might play in its diffusion. Half of the volunteers will be randomly selected to diffuse information and training related to the new BIM to their household network. In the case of the other half, their household network will receive information and training related to the new BIM by an external agent
For each Beca18 fellow in our intervention, we will map their household network within their neighborhood/community by asking them who the adult members in their household interact with in their neighborhood/community. They will also be asked to rank these household links in terms of the interaction intensity. We will select 10 to 12 members from this set and invite them to participate in the BIM training sessions.

Experimental Design Details
Randomization Method
The randomizarion has been done in office by a computer.
Randomization Unit
Our randomization unit is the household network of Beca18 fellows at Universidad de Piura. Therefore our design is a a "cluster randomized trial with person-level outcomes".
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
We aim to work with approximately 120 clusters or networks (half in the treatment group and half in the control group).
Sample size: planned number of observations
We plan to work with approximately 10-12 individuals per cluster, and therefore we aim for approximately 1200 to 1440 observations.
Sample size (or number of clusters) by treatment arms
As mentioned before, we plan to work with approximately 1200 to 1440 observations in approximately 120 clusters.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Parternship for Economic Policy Ethical Committee
IRB Approval Date
2017-08-08
IRB Approval Number
None
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS