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Are Rainwater Harvesting Techniques Profitable for Small-Scale Farmers? The Adoption and Impact of RWH Techniques in Niger
Last registered on March 14, 2018

Pre-Trial

Trial Information
General Information
Title
Are Rainwater Harvesting Techniques Profitable for Small-Scale Farmers? The Adoption and Impact of RWH Techniques in Niger
RCT ID
AEARCTR-0002560
Initial registration date
March 12, 2018
Last updated
March 14, 2018 5:09 PM EDT
Location(s)

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Primary Investigator
Affiliation
Tufts University
Other Primary Investigator(s)
PI Affiliation
Tufts University
Additional Trial Information
Status
On going
Start date
2017-12-01
End date
2020-08-31
Secondary IDs
Abstract
Due to climate change, rainfall is becoming scarcer and less reliable in many parts of the world, jeopardizing the agricultural income of already vulnerable populations. Technologies that facilitate water storage within soil and replenishment of soil nutrients could help farmers adapt to climate change. However, farmers may choose to not adopt these technologies due to high costs or a lack of training. In partnership with an international non-governmental organization, the Ministry of Environment and a research firm in Niger, this study will evaluate the adoption and impact of a rainwater harvesting technique called demi-lunes. Farmers in project villages will be randomly assigned to one of three main interventions designed to address the constraints associated with RWH technique adoption: a training, a training and unconditional cash transfer (divided into an early and a late transfer arm), and a training and conditional cash transfer. The evaluation will assess the impact of these interventions on farmers' intensive and extensive margin of adoption, agricultural practices, yields and costs. The interventions will be offered during the first year of the project. Outcomes will be tracked for a second year to measure sustained adoption and impacts.
External Link(s)
Registration Citation
Citation
Aker, Jenny and B. Kelsey Jack. 2018. "Are Rainwater Harvesting Techniques Profitable for Small-Scale Farmers? The Adoption and Impact of RWH Techniques in Niger ." AEA RCT Registry. March 14. https://doi.org/10.1257/rct.2560-1.0.
Former Citation
Aker, Jenny and B. Kelsey Jack. 2018. "Are Rainwater Harvesting Techniques Profitable for Small-Scale Farmers? The Adoption and Impact of RWH Techniques in Niger ." AEA RCT Registry. March 14. https://www.socialscienceregistry.org/trials/2560/history/26640.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
Farmers in selected villages villages in eastern Niger will be randomly assigned to one of three treatments and one control:
1) Training: Farmers will be trained on how to construct demi-lunes and their costs and benefits.
2a) Training + UCT (early): Farmers in this treatment will receive a training and an unconditional cash transfer. The UCT will be delivered shortly after training.
2b) Training + UCT (late): Farmers in this treatment will receive a training and an unconditional cash transfer. The UCT will be delivered at the same time that the CCT is paid out.
3) Training + CCT: Farmers in this treatment will receive a training and a conditional cash transfer.
4) Comparison: No training or cash transfers.

Treatments will be offered in Year 1 of the trial only. Year 2 will be used to study whether year 1 adoption outcomes are sustained.
Intervention Start Date
2018-01-15
Intervention End Date
2019-12-31
Primary Outcomes
Primary Outcomes (end points)
Demi-lune adoption (intensive and extensive) and disadoption; agricultural production; household labor allocation, labor market participation and migration; consumption and food security; soil quality.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
This research will use a cluster randomized control trial. Villages will be stratified by geographic area and and administrative type, and assigned to one of the treatments or the control.
Experimental Design Details
Not available
Randomization Method
The randomization method will be stratified randomization using min-max-T balance checks for individual and village level variables collected during the (pre-baseline) beneficiary listing.
Randomization Unit
The unit of randomization is the village.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
The number of clusters is 180 villages, with up to 16 beneficiaries per village.
Sample size: planned number of observations
The planned number of observations is 2880 individuals/households, or 16 individuals per village.
Sample size (or number of clusters) by treatment arms
The proposed sample size (village level) is:
Control: N=30
Training only: N=40
UCT-early: N=40
UCT-late: N=30
CCT: N=40
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Tufts University Social and Behavioral Ethics Review Board
IRB Approval Date
2017-11-16
IRB Approval Number
1710021
Analysis Plan

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