Facilitating uptake of resilience-enhancing technologies with stochastic benefits by subsidizing learning

Last registered on August 25, 2022
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Pre-Trial

Trial Information

General Information

Title
Facilitating uptake of resilience-enhancing technologies with stochastic benefits by subsidizing learning
RCT ID
AEARCTR-0009950
Initial registration date
August 25, 2022

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
August 25, 2022, 2:48 PM EDT

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

Locations

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Primary Investigator

Name
Jonathan Malacarne
Affiliation
University of Maine
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Other Primary Investigator(s)

PI Name
Stephen Boucher
PI Affiliation
University of California, Davis, Agricultural and Resource Economics
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PI Name
Jonathan Malacarne
PI Affiliation
University of Maine, School of Economics
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PI Name
Meizal Popat
PI Affiliation
Universidade Eduardo Mondlane
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PI Name
Lourenço Manuel
PI Affiliation
Universidade Eduardo Mondlane
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Additional Trial Information

Status
In development
Start date
2022-09-05
End date
2026-09-04
Keywords
Agriculture, Environment & Energy, Finance & Microfinance, Gender
Additional Keywords
drought tolerant seed, index insurance, soil moisture index, resilience, sustained adoption
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Emerging evidence suggests that bundling drought tolerant maize (DTM) and satellite-based index insurance (II) can foster resilience: the combined product not only helps farm households withstand shocks but allows them to deepen their investment in the wake of events that might otherwise prove crippling. These benefits, however, do not manifest themselves in all states of the world. The stochastic return on investment makes learning the value of the product challenging. This can delay the levels of sustained adoption necessary to generate large scale resilience. In this project, we will use a multi-armed randomized control trial to study subsidies to learning “through education” and “through experimentation”. Subsidy programs will be provided for two years and removed before the project’s final year. Removal of the subsidy will allow for a study of sustained adoption, both as it relates to the treatments and to the weather realizations experienced by households during the subsidy period. The project will generate additional evidence on the impact of DTM and II on maize yields, agricultural investment, and food security and builds on recent work by MRR Innovation Lab researchers and private sector partners, which led to the launch of Mozambique’s first commercial bundle of II and DTM.
External Link(s)

Registration Citation

Citation
Boucher, Stephen et al. 2022. "Facilitating uptake of resilience-enhancing technologies with stochastic benefits by subsidizing learning." AEA RCT Registry. August 25. https://doi.org/10.1257/rct.9950-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The proposed project will conduct a randomized control trial of two subsidy programs seeking to promote sustained adoption of a drought tolerant maize (DTM) and index insurance (II) bundle. The first program will be a voucher-based subsidy, reducing the cost of investing in the bundle to promote households’ experiential “learning through experimentation”. The second program will subsidize “learning through education” by providing participatory, community-based training sessions. The sessions, based on the agricultural extension model, will be designed to highlight the biological insurance inherent to DTM and the complementary protection offered by II. Experiential games – programmed for Android devices – will also be developed that allow households to “experience” many years’ worth of investment decisions, weather realizations, and returns on investment in a short, low stakes, training session.
Intervention Start Date
2022-09-05
Intervention End Date
2024-09-04

Primary Outcomes

Primary Outcomes (end points)
Area planted in maize, area planted in other staple crops, area planted in cash crops, agricultural investment in maize production, maize yields, food security status, household beliefs about the advantages of DTM relative to conventional improved maize varieties
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The treatments will be randomized at the community level according to a two-by-two factorial design, with the subsidy programs provided for two years and removed before the project’s final year. The factorial design will allow the researchers to identify the effects of each treatment component separately, as well as identify any complementarity/substitution effects among the subsidy programs. The removal of the subsidy prior to the project’s final year will allow for a study of sustained adoption.

In addition to the randomization provided by the research design, farm households will have their learning opportunities further randomized by nature. The spatial distribution of the study communities will be maximized in order to increase the chances that some households experience weather realizations that highlight the benefits of drought tolerant maize and index insurance – reinforcing the educational interventions – while other households experience weather realizations that obfuscate the benefits.
Experimental Design Details
Not available
Randomization Method
Cluster and individual level randomization will be conducted remotely by the PIs using computer software.
Randomization Unit
Voucher and community-level education treatments will be randomized at the community level. Within voucher communities, the level of subsidy will be randomized at the individual level. Within education communities, participation in a tablet-based educational game will be randomized at the individual level. Within all communities, the framing of some survey questions will be randomized at the individual level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
80 communities
Sample size: planned number of observations
1120 maize farmers
Sample size (or number of clusters) by treatment arms
20 villages control, 20 villages education, 20 villages subsidy, 20 villages education and subsidy
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We expect to be able to detect effects of 0.33 standard deviations with 80% power. Note that this involves comparisons across any two study arms: for example, subsidy only vs education only, education only vs education + subsidy, or subsidy only vs control.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Maine Institutional Review Board for the Protection of Human Subjects
IRB Approval Date
2022-08-19
IRB Approval Number
2022-05-09
Analysis Plan

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